Global Deep Learning In Computer Vision Market
Global Deep Learning In Computer Vision Market

Deep Learning In Computer Vision Comprehensive Study by Application (Image Recognition, Voice Recognition, Video Surveillance & Diagnostics, Data Mining), End-Users (Automotive, Aerospace & Defense, Healthcare, Manufacturing, Others), Solution Type (Hardware, Software, Services), Hardware Type (Central Processing Unit (CPU), Graphics Processing Unit (GPU), Field Programmable Gate Array (FPGA), Application-Specific Integrated Circuit (ASIC)) Players and Region - Global Market Outlook to 2025

Deep Learning In Computer Vision Market Segmented into XX Submarkets. | Forecast Years: 2020- 2025  

Sep 2020 Edition 245 Pages 214 Tables & Figures
  • Summary
  • Market Segments
  • Table of Content
  • List of Tables & Figures
  • Companies Mentioned
Scope of the Study

Deep learning is an intense machine learning tool that indicates exceptional execution in numerous areas. One of the best deep learning achievements is protest recognition on Convolutional Neural Networks (CNNs). The main control of CNNs is based on the fact that information representations are obtained specifically from information in a progressive layer-based structure. The past few years have shown that deep learning processes outperform traditional machine learning techniques and practices in several areas, particularly computer vision. Some of the major deep learning tools used in computer vision systems are convolutional neural networks, deep Boltzmann machines and deep belief networks, and stacked noise suppression auto-encoders.

The market study is being classified, by Application (Image Recognition, Voice Recognition, Video Surveillance & Diagnostics and Data Mining) and major geographies with country level break-up.

Accenture (Ireland), appLariat (United States), IBM (United States), Microsoft Corporation (United States), VMware (United States), Wipro (India), Appveyor (United States), Red Hat Software (United States), Atlassian (Australia), Bitrise (Hungary), CA Technologies (United States), Chef Software (United States), Circleci (United States), Clarive (Spain), Cloudbees (United States), Electric Cloud (United States), Flexagon (United States), Heroku (United States) and Infostretch (United States) are some of the key players profiled in the study. Additionally, the Players which are also part of the research are Jetbrains (Czechia), Kainos (United Kingdom), Micro Focus (United Kingdom), Shippable (United States), Spirent (United Kingdom) and Xebialabs (United States).

The companies are now exploring the market by adopting mergers & acquisitions, expansions, investments, new developments in existing products, and collaborations as their preferred strategies. The players are also exploring new geographies and industries through expansions and acquisitions so as to avail a competitive advantage through combined synergies. Research Analyst at AMA predicts that United States Players will contribute to the maximum growth of Global Deep Learning In Computer Vision market throughout the predicted period.

Segment Analysis
AdvanceMarketAnalytics has segmented the market of Global Deep Learning In Computer Vision market by Type, Application and Region.

On the basis of geography, the market of Deep Learning In Computer Vision has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, Taiwan, Australia, Rest of Asia-Pacific), Europe (Germany, France, Italy, United Kingdom, Netherlands, Rest of Europe), MEA (Middle East, Africa), North America (United States, Canada, Mexico). Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth.

Market Drivers
  • Improving Computing Power and Declining Hardware Cost
  • Rapid Improvements in Fast Information Storage Capacity
  • The Increasing Adoption of Cloud-Based Technology

Market Trend
  • High Computing Power and Parallelization
  • Rising Usage of Big Data Analytics
  • Need For Quality Check and Automation Is Increasing

Restraints
  • Lack of Technical Expertise

Opportunities
  • Growing AI Adoption in Customer-Centric Services
  • The Advancements in Smart Camera Technology and IoT

Challenges
  • Lack of User Awareness about Rapidly Changing Computer Vision Technology for Deep Learning


Market Leaders and their expansionary development strategies
In January 2016, Movidius, a U.S. based company collaborated with Google Inc. to enhance deep learning capabilities on mobile devices. In September 2016, Intel Corporation announced the acquisition of Movidius for improvising its computer vision and deep learning solutions.



Key Target Audience
Providers of Deep Learning In Computer Vision, End-Users, Potential Investors, Market Research Firms and Others

Customization in the Report Available:
The Study can be customized to meet your requirements. Please connect with our representative, who will ensure you get a report that suits your needs.
Data related to EXIM [Export- Import], production & consumption by country or regional level break-up can be provided based on client request**
** Confirmation on availability of data would be informed prior purchase
Report Objectives / Segmentation Covered
By Application
  • Image Recognition
  • Voice Recognition
  • Video Surveillance & Diagnostics
  • Data Mining
By End-Users
  • Automotive
  • Aerospace & Defense
  • Healthcare
  • Manufacturing
  • Others

By Solution Type
  • Hardware
  • Software
  • Services

By Hardware Type
  • Central Processing Unit (CPU)
  • Graphics Processing Unit (GPU)
  • Field Programmable Gate Array (FPGA)
  • Application-Specific Integrated Circuit (ASIC)

By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. Improving Computing Power and Declining Hardware Cost
      • 3.2.2. Rapid Improvements in Fast Information Storage Capacity
      • 3.2.3. The Increasing Adoption of Cloud-Based Technology
    • 3.3. Market Challenges
      • 3.3.1. Lack of User Awareness about Rapidly Changing Computer Vision Technology for Deep Learning
    • 3.4. Market Trends
      • 3.4.1. High Computing Power and Parallelization
      • 3.4.2. Rising Usage of Big Data Analytics
      • 3.4.3. Need For Quality Check and Automation Is Increasing
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global Deep Learning In Computer Vision, by Application, End-Users, Solution Type, Hardware Type and Region (value and price ) (2014-2019)
    • 5.1. Introduction
    • 5.2. Global Deep Learning In Computer Vision (Value)
      • 5.2.1. Global Deep Learning In Computer Vision by: Application (Value)
        • 5.2.1.1. Image Recognition
        • 5.2.1.2. Voice Recognition
        • 5.2.1.3. Video Surveillance & Diagnostics
        • 5.2.1.4. Data Mining
      • 5.2.2. Global Deep Learning In Computer Vision by: End-Users (Value)
        • 5.2.2.1. Automotive
        • 5.2.2.2. Aerospace & Defense
        • 5.2.2.3. Healthcare
        • 5.2.2.4. Manufacturing
        • 5.2.2.5. Others
      • 5.2.3. Global Deep Learning In Computer Vision by: Solution Type (Value)
        • 5.2.3.1. Hardware
        • 5.2.3.2. Software
        • 5.2.3.3. Services
      • 5.2.4. Global Deep Learning In Computer Vision by: Hardware Type (Value)
        • 5.2.4.1. Central Processing Unit (CPU)
        • 5.2.4.2. Graphics Processing Unit (GPU)
        • 5.2.4.3. Field Programmable Gate Array (FPGA)
        • 5.2.4.4. Application-Specific Integrated Circuit (ASIC)
      • 5.2.5. Global Deep Learning In Computer Vision Region
        • 5.2.5.1. South America
          • 5.2.5.1.1. Brazil
          • 5.2.5.1.2. Argentina
          • 5.2.5.1.3. Rest of South America
        • 5.2.5.2. Asia Pacific
          • 5.2.5.2.1. China
          • 5.2.5.2.2. Japan
          • 5.2.5.2.3. India
          • 5.2.5.2.4. South Korea
          • 5.2.5.2.5. Taiwan
          • 5.2.5.2.6. Australia
          • 5.2.5.2.7. Rest of Asia-Pacific
        • 5.2.5.3. Europe
          • 5.2.5.3.1. Germany
          • 5.2.5.3.2. France
          • 5.2.5.3.3. Italy
          • 5.2.5.3.4. United Kingdom
          • 5.2.5.3.5. Netherlands
          • 5.2.5.3.6. Rest of Europe
        • 5.2.5.4. MEA
          • 5.2.5.4.1. Middle East
          • 5.2.5.4.2. Africa
        • 5.2.5.5. North America
          • 5.2.5.5.1. United States
          • 5.2.5.5.2. Canada
          • 5.2.5.5.3. Mexico
    • 5.3. Global Deep Learning In Computer Vision (Price)
  • 6. Deep Learning In Computer Vision: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2019)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Accenture (Ireland)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. AppLariat (United States)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. IBM (United States)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. Microsoft Corporation (United States)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. VMware (United States)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. Wipro (India)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. Appveyor (United States)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. Red Hat Software (United States)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. Atlassian (Australia)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Bitrise (Hungary)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
      • 6.4.11. CA Technologies (United States)
        • 6.4.11.1. Business Overview
        • 6.4.11.2. Products/Services Offerings
        • 6.4.11.3. Financial Analysis
        • 6.4.11.4. SWOT Analysis
      • 6.4.12. Chef Software (United States)
        • 6.4.12.1. Business Overview
        • 6.4.12.2. Products/Services Offerings
        • 6.4.12.3. Financial Analysis
        • 6.4.12.4. SWOT Analysis
      • 6.4.13. Circleci (United States)
        • 6.4.13.1. Business Overview
        • 6.4.13.2. Products/Services Offerings
        • 6.4.13.3. Financial Analysis
        • 6.4.13.4. SWOT Analysis
      • 6.4.14. Clarive (Spain)
        • 6.4.14.1. Business Overview
        • 6.4.14.2. Products/Services Offerings
        • 6.4.14.3. Financial Analysis
        • 6.4.14.4. SWOT Analysis
      • 6.4.15. Cloudbees (United States)
        • 6.4.15.1. Business Overview
        • 6.4.15.2. Products/Services Offerings
        • 6.4.15.3. Financial Analysis
        • 6.4.15.4. SWOT Analysis
      • 6.4.16. Electric Cloud (United States)
        • 6.4.16.1. Business Overview
        • 6.4.16.2. Products/Services Offerings
        • 6.4.16.3. Financial Analysis
        • 6.4.16.4. SWOT Analysis
      • 6.4.17. Flexagon (United States)
        • 6.4.17.1. Business Overview
        • 6.4.17.2. Products/Services Offerings
        • 6.4.17.3. Financial Analysis
        • 6.4.17.4. SWOT Analysis
      • 6.4.18. Heroku (United States)
        • 6.4.18.1. Business Overview
        • 6.4.18.2. Products/Services Offerings
        • 6.4.18.3. Financial Analysis
        • 6.4.18.4. SWOT Analysis
      • 6.4.19. Infostretch (United States)
        • 6.4.19.1. Business Overview
        • 6.4.19.2. Products/Services Offerings
        • 6.4.19.3. Financial Analysis
        • 6.4.19.4. SWOT Analysis
  • 7. Global Deep Learning In Computer Vision Sale, by Application, End-Users, Solution Type, Hardware Type and Region (value and price ) (2020-2025)
    • 7.1. Introduction
    • 7.2. Global Deep Learning In Computer Vision (Value)
      • 7.2.1. Global Deep Learning In Computer Vision by: Application (Value)
        • 7.2.1.1. Image Recognition
        • 7.2.1.2. Voice Recognition
        • 7.2.1.3. Video Surveillance & Diagnostics
        • 7.2.1.4. Data Mining
      • 7.2.2. Global Deep Learning In Computer Vision by: End-Users (Value)
        • 7.2.2.1. Automotive
        • 7.2.2.2. Aerospace & Defense
        • 7.2.2.3. Healthcare
        • 7.2.2.4. Manufacturing
        • 7.2.2.5. Others
      • 7.2.3. Global Deep Learning In Computer Vision by: Solution Type (Value)
        • 7.2.3.1. Hardware
        • 7.2.3.2. Software
        • 7.2.3.3. Services
      • 7.2.4. Global Deep Learning In Computer Vision by: Hardware Type (Value)
        • 7.2.4.1. Central Processing Unit (CPU)
        • 7.2.4.2. Graphics Processing Unit (GPU)
        • 7.2.4.3. Field Programmable Gate Array (FPGA)
        • 7.2.4.4. Application-Specific Integrated Circuit (ASIC)
      • 7.2.5. Global Deep Learning In Computer Vision Region
        • 7.2.5.1. South America
          • 7.2.5.1.1. Brazil
          • 7.2.5.1.2. Argentina
          • 7.2.5.1.3. Rest of South America
        • 7.2.5.2. Asia Pacific
          • 7.2.5.2.1. China
          • 7.2.5.2.2. Japan
          • 7.2.5.2.3. India
          • 7.2.5.2.4. South Korea
          • 7.2.5.2.5. Taiwan
          • 7.2.5.2.6. Australia
          • 7.2.5.2.7. Rest of Asia-Pacific
        • 7.2.5.3. Europe
          • 7.2.5.3.1. Germany
          • 7.2.5.3.2. France
          • 7.2.5.3.3. Italy
          • 7.2.5.3.4. United Kingdom
          • 7.2.5.3.5. Netherlands
          • 7.2.5.3.6. Rest of Europe
        • 7.2.5.4. MEA
          • 7.2.5.4.1. Middle East
          • 7.2.5.4.2. Africa
        • 7.2.5.5. North America
          • 7.2.5.5.1. United States
          • 7.2.5.5.2. Canada
          • 7.2.5.5.3. Mexico
    • 7.3. Global Deep Learning In Computer Vision (Price)
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. Deep Learning In Computer Vision: by Application(USD Million)
  • Table 2. Deep Learning In Computer Vision Image Recognition , by Region USD Million (2014-2019)
  • Table 3. Deep Learning In Computer Vision Voice Recognition , by Region USD Million (2014-2019)
  • Table 4. Deep Learning In Computer Vision Video Surveillance & Diagnostics , by Region USD Million (2014-2019)
  • Table 5. Deep Learning In Computer Vision Data Mining , by Region USD Million (2014-2019)
  • Table 6. Deep Learning In Computer Vision: by End-Users(USD Million)
  • Table 7. Deep Learning In Computer Vision Automotive , by Region USD Million (2014-2019)
  • Table 8. Deep Learning In Computer Vision Aerospace & Defense , by Region USD Million (2014-2019)
  • Table 9. Deep Learning In Computer Vision Healthcare , by Region USD Million (2014-2019)
  • Table 10. Deep Learning In Computer Vision Manufacturing , by Region USD Million (2014-2019)
  • Table 11. Deep Learning In Computer Vision Others , by Region USD Million (2014-2019)
  • Table 12. Deep Learning In Computer Vision: by Solution Type(USD Million)
  • Table 13. Deep Learning In Computer Vision Hardware , by Region USD Million (2014-2019)
  • Table 14. Deep Learning In Computer Vision Software , by Region USD Million (2014-2019)
  • Table 15. Deep Learning In Computer Vision Services , by Region USD Million (2014-2019)
  • Table 16. Deep Learning In Computer Vision: by Hardware Type(USD Million)
  • Table 17. Deep Learning In Computer Vision Central Processing Unit (CPU) , by Region USD Million (2014-2019)
  • Table 18. Deep Learning In Computer Vision Graphics Processing Unit (GPU) , by Region USD Million (2014-2019)
  • Table 19. Deep Learning In Computer Vision Field Programmable Gate Array (FPGA) , by Region USD Million (2014-2019)
  • Table 20. Deep Learning In Computer Vision Application-Specific Integrated Circuit (ASIC) , by Region USD Million (2014-2019)
  • Table 21. South America Deep Learning In Computer Vision, by Country USD Million (2014-2019)
  • Table 22. South America Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 23. South America Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 24. South America Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 25. South America Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 26. Brazil Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 27. Brazil Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 28. Brazil Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 29. Brazil Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 30. Argentina Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 31. Argentina Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 32. Argentina Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 33. Argentina Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 34. Rest of South America Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 35. Rest of South America Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 36. Rest of South America Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 37. Rest of South America Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 38. Asia Pacific Deep Learning In Computer Vision, by Country USD Million (2014-2019)
  • Table 39. Asia Pacific Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 40. Asia Pacific Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 41. Asia Pacific Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 42. Asia Pacific Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 43. China Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 44. China Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 45. China Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 46. China Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 47. Japan Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 48. Japan Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 49. Japan Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 50. Japan Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 51. India Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 52. India Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 53. India Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 54. India Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 55. South Korea Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 56. South Korea Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 57. South Korea Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 58. South Korea Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 59. Taiwan Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 60. Taiwan Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 61. Taiwan Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 62. Taiwan Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 63. Australia Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 64. Australia Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 65. Australia Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 66. Australia Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 67. Rest of Asia-Pacific Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 68. Rest of Asia-Pacific Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 69. Rest of Asia-Pacific Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 70. Rest of Asia-Pacific Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 71. Europe Deep Learning In Computer Vision, by Country USD Million (2014-2019)
  • Table 72. Europe Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 73. Europe Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 74. Europe Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 75. Europe Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 76. Germany Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 77. Germany Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 78. Germany Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 79. Germany Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 80. France Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 81. France Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 82. France Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 83. France Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 84. Italy Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 85. Italy Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 86. Italy Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 87. Italy Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 88. United Kingdom Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 89. United Kingdom Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 90. United Kingdom Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 91. United Kingdom Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 92. Netherlands Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 93. Netherlands Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 94. Netherlands Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 95. Netherlands Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 96. Rest of Europe Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 97. Rest of Europe Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 98. Rest of Europe Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 99. Rest of Europe Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 100. MEA Deep Learning In Computer Vision, by Country USD Million (2014-2019)
  • Table 101. MEA Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 102. MEA Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 103. MEA Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 104. MEA Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 105. Middle East Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 106. Middle East Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 107. Middle East Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 108. Middle East Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 109. Africa Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 110. Africa Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 111. Africa Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 112. Africa Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 113. North America Deep Learning In Computer Vision, by Country USD Million (2014-2019)
  • Table 114. North America Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 115. North America Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 116. North America Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 117. North America Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 118. United States Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 119. United States Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 120. United States Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 121. United States Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 122. Canada Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 123. Canada Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 124. Canada Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 125. Canada Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 126. Mexico Deep Learning In Computer Vision, by Application USD Million (2014-2019)
  • Table 127. Mexico Deep Learning In Computer Vision, by End-Users USD Million (2014-2019)
  • Table 128. Mexico Deep Learning In Computer Vision, by Solution Type USD Million (2014-2019)
  • Table 129. Mexico Deep Learning In Computer Vision, by Hardware Type USD Million (2014-2019)
  • Table 130. Company Basic Information, Sales Area and Its Competitors
  • Table 131. Company Basic Information, Sales Area and Its Competitors
  • Table 132. Company Basic Information, Sales Area and Its Competitors
  • Table 133. Company Basic Information, Sales Area and Its Competitors
  • Table 134. Company Basic Information, Sales Area and Its Competitors
  • Table 135. Company Basic Information, Sales Area and Its Competitors
  • Table 136. Company Basic Information, Sales Area and Its Competitors
  • Table 137. Company Basic Information, Sales Area and Its Competitors
  • Table 138. Company Basic Information, Sales Area and Its Competitors
  • Table 139. Company Basic Information, Sales Area and Its Competitors
  • Table 140. Company Basic Information, Sales Area and Its Competitors
  • Table 141. Company Basic Information, Sales Area and Its Competitors
  • Table 142. Company Basic Information, Sales Area and Its Competitors
  • Table 143. Company Basic Information, Sales Area and Its Competitors
  • Table 144. Company Basic Information, Sales Area and Its Competitors
  • Table 145. Company Basic Information, Sales Area and Its Competitors
  • Table 146. Company Basic Information, Sales Area and Its Competitors
  • Table 147. Company Basic Information, Sales Area and Its Competitors
  • Table 148. Company Basic Information, Sales Area and Its Competitors
  • Table 149. Deep Learning In Computer Vision: by Application(USD Million)
  • Table 150. Deep Learning In Computer Vision Image Recognition , by Region USD Million (2020-2025)
  • Table 151. Deep Learning In Computer Vision Voice Recognition , by Region USD Million (2020-2025)
  • Table 152. Deep Learning In Computer Vision Video Surveillance & Diagnostics , by Region USD Million (2020-2025)
  • Table 153. Deep Learning In Computer Vision Data Mining , by Region USD Million (2020-2025)
  • Table 154. Deep Learning In Computer Vision: by End-Users(USD Million)
  • Table 155. Deep Learning In Computer Vision Automotive , by Region USD Million (2020-2025)
  • Table 156. Deep Learning In Computer Vision Aerospace & Defense , by Region USD Million (2020-2025)
  • Table 157. Deep Learning In Computer Vision Healthcare , by Region USD Million (2020-2025)
  • Table 158. Deep Learning In Computer Vision Manufacturing , by Region USD Million (2020-2025)
  • Table 159. Deep Learning In Computer Vision Others , by Region USD Million (2020-2025)
  • Table 160. Deep Learning In Computer Vision: by Solution Type(USD Million)
  • Table 161. Deep Learning In Computer Vision Hardware , by Region USD Million (2020-2025)
  • Table 162. Deep Learning In Computer Vision Software , by Region USD Million (2020-2025)
  • Table 163. Deep Learning In Computer Vision Services , by Region USD Million (2020-2025)
  • Table 164. Deep Learning In Computer Vision: by Hardware Type(USD Million)
  • Table 165. Deep Learning In Computer Vision Central Processing Unit (CPU) , by Region USD Million (2020-2025)
  • Table 166. Deep Learning In Computer Vision Graphics Processing Unit (GPU) , by Region USD Million (2020-2025)
  • Table 167. Deep Learning In Computer Vision Field Programmable Gate Array (FPGA) , by Region USD Million (2020-2025)
  • Table 168. Deep Learning In Computer Vision Application-Specific Integrated Circuit (ASIC) , by Region USD Million (2020-2025)
  • Table 169. South America Deep Learning In Computer Vision, by Country USD Million (2020-2025)
  • Table 170. South America Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 171. South America Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 172. South America Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 173. South America Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 174. Brazil Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 175. Brazil Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 176. Brazil Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 177. Brazil Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 178. Argentina Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 179. Argentina Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 180. Argentina Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 181. Argentina Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 182. Rest of South America Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 183. Rest of South America Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 184. Rest of South America Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 185. Rest of South America Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 186. Asia Pacific Deep Learning In Computer Vision, by Country USD Million (2020-2025)
  • Table 187. Asia Pacific Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 188. Asia Pacific Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 189. Asia Pacific Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 190. Asia Pacific Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 191. China Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 192. China Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 193. China Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 194. China Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 195. Japan Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 196. Japan Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 197. Japan Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 198. Japan Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 199. India Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 200. India Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 201. India Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 202. India Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 203. South Korea Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 204. South Korea Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 205. South Korea Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 206. South Korea Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 207. Taiwan Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 208. Taiwan Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 209. Taiwan Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 210. Taiwan Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 211. Australia Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 212. Australia Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 213. Australia Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 214. Australia Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 215. Rest of Asia-Pacific Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 216. Rest of Asia-Pacific Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 217. Rest of Asia-Pacific Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 218. Rest of Asia-Pacific Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 219. Europe Deep Learning In Computer Vision, by Country USD Million (2020-2025)
  • Table 220. Europe Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 221. Europe Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 222. Europe Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 223. Europe Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 224. Germany Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 225. Germany Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 226. Germany Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 227. Germany Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 228. France Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 229. France Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 230. France Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 231. France Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 232. Italy Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 233. Italy Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 234. Italy Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 235. Italy Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 236. United Kingdom Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 237. United Kingdom Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 238. United Kingdom Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 239. United Kingdom Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 240. Netherlands Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 241. Netherlands Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 242. Netherlands Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 243. Netherlands Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 244. Rest of Europe Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 245. Rest of Europe Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 246. Rest of Europe Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 247. Rest of Europe Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 248. MEA Deep Learning In Computer Vision, by Country USD Million (2020-2025)
  • Table 249. MEA Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 250. MEA Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 251. MEA Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 252. MEA Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 253. Middle East Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 254. Middle East Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 255. Middle East Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 256. Middle East Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 257. Africa Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 258. Africa Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 259. Africa Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 260. Africa Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 261. North America Deep Learning In Computer Vision, by Country USD Million (2020-2025)
  • Table 262. North America Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 263. North America Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 264. North America Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 265. North America Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 266. United States Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 267. United States Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 268. United States Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 269. United States Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 270. Canada Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 271. Canada Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 272. Canada Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 273. Canada Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 274. Mexico Deep Learning In Computer Vision, by Application USD Million (2020-2025)
  • Table 275. Mexico Deep Learning In Computer Vision, by End-Users USD Million (2020-2025)
  • Table 276. Mexico Deep Learning In Computer Vision, by Solution Type USD Million (2020-2025)
  • Table 277. Mexico Deep Learning In Computer Vision, by Hardware Type USD Million (2020-2025)
  • Table 278. Research Programs/Design for This Report
  • Table 279. Key Data Information from Secondary Sources
  • Table 280. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global Deep Learning In Computer Vision: by Application USD Million (2014-2019)
  • Figure 5. Global Deep Learning In Computer Vision: by End-Users USD Million (2014-2019)
  • Figure 6. Global Deep Learning In Computer Vision: by Solution Type USD Million (2014-2019)
  • Figure 7. Global Deep Learning In Computer Vision: by Hardware Type USD Million (2014-2019)
  • Figure 8. South America Deep Learning In Computer Vision Share (%), by Country
  • Figure 9. Asia Pacific Deep Learning In Computer Vision Share (%), by Country
  • Figure 10. Europe Deep Learning In Computer Vision Share (%), by Country
  • Figure 11. MEA Deep Learning In Computer Vision Share (%), by Country
  • Figure 12. North America Deep Learning In Computer Vision Share (%), by Country
  • Figure 13. Global Deep Learning In Computer Vision share by Players 2019 (%)
  • Figure 14. Global Deep Learning In Computer Vision share by Players (Top 3) 2019(%)
  • Figure 15. Global Deep Learning In Computer Vision share by Players (Top 5) 2019(%)
  • Figure 16. BCG Matrix for key Companies
  • Figure 17. Accenture (Ireland) Revenue, Net Income and Gross profit
  • Figure 18. Accenture (Ireland) Revenue: by Geography 2019
  • Figure 19. AppLariat (United States) Revenue, Net Income and Gross profit
  • Figure 20. AppLariat (United States) Revenue: by Geography 2019
  • Figure 21. IBM (United States) Revenue, Net Income and Gross profit
  • Figure 22. IBM (United States) Revenue: by Geography 2019
  • Figure 23. Microsoft Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 24. Microsoft Corporation (United States) Revenue: by Geography 2019
  • Figure 25. VMware (United States) Revenue, Net Income and Gross profit
  • Figure 26. VMware (United States) Revenue: by Geography 2019
  • Figure 27. Wipro (India) Revenue, Net Income and Gross profit
  • Figure 28. Wipro (India) Revenue: by Geography 2019
  • Figure 29. Appveyor (United States) Revenue, Net Income and Gross profit
  • Figure 30. Appveyor (United States) Revenue: by Geography 2019
  • Figure 31. Red Hat Software (United States) Revenue, Net Income and Gross profit
  • Figure 32. Red Hat Software (United States) Revenue: by Geography 2019
  • Figure 33. Atlassian (Australia) Revenue, Net Income and Gross profit
  • Figure 34. Atlassian (Australia) Revenue: by Geography 2019
  • Figure 35. Bitrise (Hungary) Revenue, Net Income and Gross profit
  • Figure 36. Bitrise (Hungary) Revenue: by Geography 2019
  • Figure 37. CA Technologies (United States) Revenue, Net Income and Gross profit
  • Figure 38. CA Technologies (United States) Revenue: by Geography 2019
  • Figure 39. Chef Software (United States) Revenue, Net Income and Gross profit
  • Figure 40. Chef Software (United States) Revenue: by Geography 2019
  • Figure 41. Circleci (United States) Revenue, Net Income and Gross profit
  • Figure 42. Circleci (United States) Revenue: by Geography 2019
  • Figure 43. Clarive (Spain) Revenue, Net Income and Gross profit
  • Figure 44. Clarive (Spain) Revenue: by Geography 2019
  • Figure 45. Cloudbees (United States) Revenue, Net Income and Gross profit
  • Figure 46. Cloudbees (United States) Revenue: by Geography 2019
  • Figure 47. Electric Cloud (United States) Revenue, Net Income and Gross profit
  • Figure 48. Electric Cloud (United States) Revenue: by Geography 2019
  • Figure 49. Flexagon (United States) Revenue, Net Income and Gross profit
  • Figure 50. Flexagon (United States) Revenue: by Geography 2019
  • Figure 51. Heroku (United States) Revenue, Net Income and Gross profit
  • Figure 52. Heroku (United States) Revenue: by Geography 2019
  • Figure 53. Infostretch (United States) Revenue, Net Income and Gross profit
  • Figure 54. Infostretch (United States) Revenue: by Geography 2019
  • Figure 55. Global Deep Learning In Computer Vision: by Application USD Million (2020-2025)
  • Figure 56. Global Deep Learning In Computer Vision: by End-Users USD Million (2020-2025)
  • Figure 57. Global Deep Learning In Computer Vision: by Solution Type USD Million (2020-2025)
  • Figure 58. Global Deep Learning In Computer Vision: by Hardware Type USD Million (2020-2025)
  • Figure 59. South America Deep Learning In Computer Vision Share (%), by Country
  • Figure 60. Asia Pacific Deep Learning In Computer Vision Share (%), by Country
  • Figure 61. Europe Deep Learning In Computer Vision Share (%), by Country
  • Figure 62. MEA Deep Learning In Computer Vision Share (%), by Country
  • Figure 63. North America Deep Learning In Computer Vision Share (%), by Country
Some of the key companies/manufacturers profiled in the report
  • Accenture (Ireland)
  • appLariat (United States)
  • IBM (United States)
  • Microsoft Corporation (United States)
  • VMware (United States)
  • Wipro (India)
  • Appveyor (United States)
  • Red Hat Software (United States)
  • Atlassian (Australia)
  • Bitrise (Hungary)
  • CA Technologies (United States)
  • Chef Software (United States)
  • Circleci (United States)
  • Clarive (Spain)
  • Cloudbees (United States)
  • Electric Cloud (United States)
  • Flexagon (United States)
  • Heroku (United States)
  • Infostretch (United States)
Additional players considered in the study are as follows:
Jetbrains (Czechia) , Kainos (United Kingdom) , Micro Focus (United Kingdom) , Shippable (United States) , Spirent (United Kingdom) , Xebialabs (United States)
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