Market Highlights: 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 that includes 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).
Key Players: The prominent players in the Deep Learning In Computer Vision are 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).
Major Market Development Highlights 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 Questions Answered in the Report What will the Deep Learning In Computer Vision Market size and the growth rate be in Future? What are the key factors driving the Deep Learning In Computer Vision Market? What are the key market trends and macro-economic impacting the growth of the Deep Learning In Computer Vision Market? What are the challenges to market growth? Who are the key vendors in the Deep Learning In Computer Vision Market? What are the market opportunities and threats faced by the vendors in the Deep Learning In Computer Vision Market? Trending factors influencing the market shares of the Players. What are the key outcomes of the five forces analysis of the Deep Learning In Computer Vision Market?
Research Methodology: The top-down and bottom-up approaches are used to estimate and validate the size of the Global Deep Learning In Computer Vision market. In order to reach an exhaustive list of functional and relevant players various industry classification standards are closely followed such as NAICS, ICB, SIC to penetrate deep in important geographies by players and a thorough validation test is conducted to reach most relevant players for survey in Deep Learning In Computer Vision market. In order to make priority list sorting is done based on revenue generated based on latest reporting with the help of paid databases such as Factiva, Bloomberg etc. Finally the questionnaire is set and specifically designed to address all the necessities for primary data collection after getting prior appointment by targeting key target audience that includes Providers of Deep Learning In Computer Vision, End-Users, Potential Investors, Market Research Firms and Others. This helps us to gather the data for the players revenue, operating cycle and expense, profit along with product or service growth etc. Almost 70-80% of data is collected through primary medium and further validation is done through various secondary sources that includes Regulators, World Bank, Association, Company Website, SEC filings, OTC BB, Annual reports, press releases etc.