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Data Annotation Tools Market Overview by Future Growth Analysis and Demand Forecast to 2026

Author : Ronak Bora | Published Date : 2020-08-19 

Global data annotation tools market growth is characterized by the seamless transition of raw unstructured data into insightful and useful Business Intelligence (BI) by machine learning facilities with human guidance, through the use of data annotation tools. Data annotation refers to the labelling of data in myriad forms, from video, audio, image, text, etc.

With regards to data type, the data annotation tools market is categorized into image/video, audio and text. Of these, the image/video data annotation tools industry from the polygonal annotation segment is poised to depict a CAGR of nearly 40% through 2026. This growth is ascribed largely to accurate object detection as well as image/video localization properties.

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Data Annotation Tools market is projected to surpass USD 5 billion by 2026. The market growth is attributed to the steadily growing uptake of data annotation tools by healthcare institutions for medical image labeling and classification of medical literature. The proliferation of wearable health devices and the surging volumes of digital medical information have made it increasingly difficult for data scientists to label data manually. These tools are helping healthcare organizations in addressing these issues by providing accurate & high-quality labeled medical data with minimum assistance from medical experts. For instance, in October 2019, TrainingData.io, a startup funded by the NVIDIA Inception startup accelerator program, launched a web interface for medical data labeling, which claims to speed up labeling by up to ten times and reduce the labeling error rate by more than 15%. Furthermore, data annotation tools are empowering sophisticated AI algorithms to accurately detect signs of diseases and medical issues without the need for specialized medical staff. For instance, in September 2019, GE Healthcare developed an AI algorithm for detecting collapsed lungs through X-ray images. The labeled medical data was provided by UC San Francisco.

Some major findings of the data annotation tools market report include:

  • With the dynamically changing technology landscape in the automotive sector, many automobile manufacturers are focusing on leveraging data annotation tools to accelerate the development of autonomous technologies
  • The growing importance of accurately-labeled textual data to develop novel technologies such as natural language generation, text-to-speech, and voice recognition will create a positive outlook for the data annotation tools market
  • Data scientists are reaping benefits of automated data labeling tools, which will facilitate quick & accurate labeling of large-scale datasets including support for big data and Hadoop platforms
  • Manual data annotation tools require the presence of a human data labeler for the annotation of data but are highly accurate compared to automated data labeling tools due to the involvement of a human domain expert
  • The rising penetration of machine learning and artificial intelligence technologies in business environments to increase competitive advantage and improve efficiency will continue to drive the adoption of data labeling solutions
  • Some of the leading market players are Alegion, Inc., Appen Limited, Amazon Web Services, Inc., Clickworker GmbH, CloudApp, Inc., CloudFactory Limited, Cogito, Google LLC, Hive, IBM Corporation, iMerit, Labelbox, Inc., LionBridge AI, Mighty AI, MonkeyLearn Inc., Neurala, Inc., Playment Inc., Samasource Inc., Scale, Inc., Trilldata Technologies Pvt. Ltd., and Webtunix AI, etc.
  • Data annotation tools providers are focusing on strategic collaborations and long-term contracts with clients to gain the market share

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Companies operating in the data annotation tools industry are focusing on various business growth strategies, including investments in new data labeling solutions, strengthening partner network, and geographical expansion. Through such strategic moves, companies are trying to gain a broader market share and maintain their leadership in the market. For instance, in October 2018, Playment, a machine learning & data annotation startup, partnered with Ouster, a leading manufacturer of LiDAR sensors, to annotate and calibrate 3D imagery captured by its sensors. The partnership helped the company leverage accurately labeled training data for improving the deep learning systems built around autonomous technologies. Furthermore, several key players, such as Google, Microsoft, and Amazon, are offering data labeling platforms for procuring data labeling services on a subscription basis. For instance, in November 2019, Google launched the AI Platform Data Labeling Service, which offers enterprises a platform for requesting human labelers to annotate their custom data as requirements. With increasing investments in AI technologies and the growing importance of data labeling in sophisticated technology development including autonomous vehicles and automated medical diagnosis, the data annotation tools market is expected to witness a sharp increase over the forecast timespan.

Table of Contents (ToC) of the report:

Chapter 5.    Data Annotation Tools Market, By Data Type

5.1.    Key trends, by data type

5.2.    Image/video

5.2.1. Market estimates and forecast, 2015 – 2026

5.2.2. Bounding box

5.2.2.1.    Market estimates and forecast, 2015 – 2026

5.2.3. Semantic annotation

5.2.3.1.    Market estimates and forecast, 2015 – 2026

5.2.4. Polygon annotation

5.2.4.1.    Market estimates and forecast, 2015 – 2026

5.2.5. Line annotation

5.2.5.1.    Market estimates and forecast, 2015 – 2026

5.2.6. Others

5.2.6.1.    Market estimates and forecast, 2015 – 2026

5.3.    Text

5.3.1. Market estimates and forecast, 2015 – 2026

5.4.    Audio

5.4.1. Market estimates and forecast, 2015 – 2026

Chapter 6.    Data Annotation Tools Market, By Annotation Approach

6.1.    Key trends, by annotation approach

6.2.    Manual annotation

6.2.1. Market estimates and forecast, 2015 – 2026

6.3.    Automated annotation

6.3.1. Market estimates and forecast, 2015 – 2026

Browse complete Table of Contents (ToC) of this research report @ https://www.decresearch.com/toc/detail/data-annotation-tools-market

About Author

Ronak Bora

Ronak Bora

A graduate in Electronics Engineering, Ronak writes for fractovia and carries a rich experience in digital marketing, exploring how the online world works from a technical and marketing perspective. His other areas of interest include reading, music, and sport. [email protected] | https://twitter.com/RonakBora26

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