Scope of the Study
The data annotation tools are used for processing or labeling data machine learning and training different computer vision models. Data can be in any form that a human might understand such as text, audio, images or video, tabular data and other types of data. These tools can be majorly used by a data scientist to clean the data and annotated data to train machine learning models and also used in deep learning. There are various types and uses for data annotation in machine learning including classification of image or text, detection of an object and segmentation and other types of tools. However, all of these tools are built with direct manipulation via Graphical User Interfaces (GUI). Data Annotation plays major role in machine learning and deep learning applications.
The market study is being classified and major geographies with country level break-up.
Amazon Mechanical Turk (United States), Lionbridge AI (United States), Edgecase (United States), Scale AI (United States), CloudApp, Inc. (United States), Hive AI (United States), Figure Eight (United States), Humans in the Loop (Bulgaria), Clickworker (Germany), Appen (Australia), Dbrain (Russia), Webtunix AI (United States), IBM Corporation (United States), Labelbox, Inc. (United States), Trantor (United States), Netguru (Poland) and DataLoop (Israel) are some of the key players profiled in the study.
Research Analyst at AMA predicts that North America and Europe Players will contribute to the maximum growth of Global Data Annotation Tools market throughout the predicted period.
AdvanceMarketAnalytics has segmented the market of Global Data Annotation Tools market by Type, Application and Region.
On the basis of geography, the market of Data Annotation Tools 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.
- Rapid Growth in Artificial Intelligence is a Significantly Growing Demand for Data Annotation Tools
- Data Annotation Tools Are Extremely Used in Various Field Such as Self Driving, Robotics, Automotive and Healthcare
- Rising Demand for Annotated Data to Improve the Machine Learning Models
- AI Models or Automated Applications Provide a Totally Different and Seamless Experience for End-Users
- Data Annotation Tools are Trending Due to the Online Search Engines Needs Huge Amount of Datasets to Improve the Quality of Its Search
- Automatic Annotation Technique is the Most Efficient and Requires Least Time
- Rising Trend of Computer Vision Annotation Tool (CVAT) Which Helps to Annotate Image and Video for Computer Vision Algorithms
- Data Annotation is Time Consuming and Worth the Trouble
- Manual Data Annotation is Very Slow Process
- Innovation in Artificial Intelligence and Machine Learning Technology which Provides the Advantages to Different Fields Globally
- Data Annotation Tools is Widely Used Self-Driving Vehicles
- The Data Annotation is Crucial Issue behind a Models Accuracy
- Automatic Image Annotation is Not Suitable for Unsupervised Learning Process
Market Leaders and their expansionary development strategies
In July 2019, dSPACE, the leading provider of solutions for the development of network, autonomous, and electrically powered vehicles company acquired the start-up company understand.ai. Both will invest in core tasks ‘AI application’ and ‘cloud-based tools’.
In January 2020, IBM, an American multinational information technology company launched an annotation tool that taps artificial intelligence (AI) to label images. The new tool uses AI to helps developers to annotate data without manually drawing labels on the complete dataset of images. Simply select the “Auto label” button from the dashboard automatically labels uploaded image samples. This is optimized for data-hungry machine learning and cloud-native workloads. and In March 2019, Alegion, a leading training data preparation platform for artificial intelligence (AI) and machine learning launched its new suite of image and video annotation tools for training data in computer vision initiatives. These new capabilities are specialized for data tasks like image classification, object localization, and semantic segmentation, and are being used by customers across retail, automotive, technology, government, and financial services.
Key Target AudienceSoftware Development Company, Data Annotation Tools Provider, Artificial Intelligence Companies, Data Science Consulting Firm, End-Users and Others
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