Increasing spending on research and development in the autonomous vehicle supply sector

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Global Data Collection and Labeling Market

Global Data Collection and Labeling Market

Global Data Collection and Labeling Market

Dublin, September 26, 2022 (GLOBE NEWSWIRE) – The “Data Collection and Labeling, Market Size, Sharing and Trends Analysis Report by Data Type (audio, image/video, text), by vertical (IT, Retail and E-Commerce), by Region, and Segments Forecast, 2022-2030” Report added to ResearchAndMarkets.com Show.

The global data collection and labeling market size is expected to reach US$12.75 billion by 2030, according to this report. The market is expected to expand at a compound annual growth rate of 25.1% from 2022 to 2030. Data collection and labeling refers to the collection of data sets from online and other sources and their classification based on their nature, data type, and feature. Data collection and annotation, combined with AI technology, has created valuable growth opportunities in many sectors, such as gaming, social networking, and e-commerce.

For example, Twitter and Facebook, two major social networking platforms, have made use of image processing technology to engage the audience. Companies use data classification platforms to select raw data for a machine learning model. Text, movies, audio and other elements are the raw data.

The advent of digital capture devices, especially cameras built into smartphones, has led to an exponential growth in the volume of digital content in the form of photos and videos. Much visual and digital information is captured and shared through many applications, websites, social networks, and other digital channels. Many companies have taken advantage of this online content to provide smarter and better services to their customers using data annotations. For example, Scale AI, Inc. , the US-based startup tech company, provides valuable data profiling services to its self-driving customers, including Waymo LLC; Lyft, Inc. Zox. and Toyota Research Institute.

However, data cleaning is still a huge challenge that data naming is involved in. Also, given the time, complexity, and cost associated with developing machine learning models, many companies may not have the resources that can produce acceptable and accurate results. Therefore, many companies are taking strategic initiatives to expand their AI-based data collection business. For example, in July 2020, Microsoft acquired Orions Digital Systems, Inc. , a US-based data management solutions provider, to enhance the capabilities of the Dynamics 365 Connected Store. This acquisition is expected to increase the use of computer vision and IoT sensors to help retailers better understand customer behavior and manage their physical spaces.

Highlights of the Data Collection and Labeling market report:

  • Automated image curation offered by cloud-based applications and carriers is one of the most popular uses of data collection that has improved users’ experience and attracted customers to this technology.

  • Many benefits such as improved security and identification automation encourage the implementation of facial recognition in public places or important events

  • The emergence of large-scale artificial intelligence and machine learning systems hosted on the cloud and provided by tech giants has led to the implementation of data annotation with multiple functions, such as facial recognition, object recognition, and feature detection

  • The increasing integration of digital image processing and mobile computing platforms into many digital shopping and document verification applications is driving market growth

market dynamics

Market Drivers

  • Increasing need to make text/image more interactive and interactive

  • The rapid breakthrough of artificial intelligence and machine learning

  • Increased R&D spending on developing autonomous vehicles

adjust the market

Main topics covered:

Chapter 1 Methodology and Scope

Chapter 2 Executive Summary

Chapter 3 Market Variables, Trends and Scope

Chapter 4 Data Collection and Market Labeling: Data Type Estimates and Trend Analysis

Chapter 5 Data Collection and Market Labeling: Vertical Estimates and Trend Analysis

Chapter 6 Data Collection and Market Labeling: Regional Estimates and Trend Analysis

Chapter 7 Competitive Scene

mentioned companies

  • ABIN LIMITED

  • Reality AI

  • Globalme Localization Inc.

  • global technology solutions

  • Legion

  • Labelbox, Inc.

  • Doubility, Inc.

  • AI Scale, Inc.

  • Trilldata Technologies Pvt. Ltd.

  • Playment Company

For more information about this report visit https://www.researchandmarkets.com/r/8u6rz9

Attached

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