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  • Global Data Annotation Tools Market

Future Growth of Data Annotation Tools Market Explored; Opportunity Ahead of Earnings

Data Annotation Tools Market Latest Edition Published with Forecast to 2028
  • Nov 29, 2023
  • Masarat
  • Application Software
  • AMA Research
Market Highlights:
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 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 Data Annotation Tools are 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).

The End-User Industry, such as Self-Driving, is boosting the Data Annotation Tools market. Additionally, the rising demand from SMEs and various industry verticals, macro-economic growth are the prime factors driving the growth of the market.

The Annotation Tools, such as Bounding Boxes, is boosting the Data Annotation Tools market. Additionally, the rising demand from SMEs and various industry verticals, macro-economic growth are the prime factors driving the growth of the market.

The Data Annotation Types, such as Image, is boosting the Data Annotation Tools market. Additionally, the rising demand from SMEs and various industry verticals, macro-economic growth are the prime factors driving the growth of the market.

The Price, such as Community Edition, is boosting the Data Annotation Tools market. Additionally, the rising demand from SMEs and various industry verticals, macro-economic growth are the prime factors driving the growth of the market.

The Data Annotation Techniques, such as Manual, is boosting the Data Annotation Tools market. Additionally, the rising demand from SMEs and various industry verticals, macro-economic growth are the prime factors driving the growth of the market.

Major Market Development Highlights
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 Questions Answered in the Report
What will the Data Annotation Tools Market size and the growth rate be in Future?
What are the key factors driving the Data Annotation Tools Market?
What are the key market trends and macro-economic impacting the growth of the Data Annotation Tools Market?
What are the challenges to market growth?
Who are the key vendors in the Data Annotation Tools Market?
What are the market opportunities and threats faced by the vendors in the Data Annotation Tools Market?
Trending factors influencing the market shares of the Players.
What are the key outcomes of the five forces analysis of the Data Annotation Tools Market?

Refer complete Table of Content of Data Annotation Tools Market Study

Research Methodology:
The top-down and bottom-up approaches are used to estimate and validate the size of the Global Data Annotation Tools 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 Data Annotation Tools 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 Software Development Company, Data Annotation Tools Provider, Artificial Intelligence Companies, Data Science Consulting Firm, End-Users 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.

Praveen Kumar

Head & Director of Sales
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