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Artificial Intelligence (AI) in Computer Vision Market Size to Reach USD 130.57 Billion by 2030 Growing Demand for Computer Vision Systems in Automotive Applications

Artificial Intelligence (AI) in Computer Vision Market Size – USD 15.87 Billion in 2021, Market Growth – at a CAGR of 26.3%, Market Trends – High demand for AI in the market of computer vision

Rising demand for quality inspection and automation and government initiatives for the development of AI-related technologies are driving AI in computer vision market revenue growth

The Global Artificial Intelligence (AI) in Computer Vision Market The size is expected to reach USD 130.57 billion in 2030 and register a CAGR of 26.3% over the forecast period, according to the latest report from Reports and Data. Rising demand for computer vision systems in automotive applications and rising demand for emotional AI are key factors driving the revenue growth in the AI ​​in computer vision market.

AI is the ability of a computer or computerized robotic system to manage data, produce results, and provide problem-solving results similar to human thought processes. Computer vision is a branch of computer science that aims to simulate the complexity of the human vision system, allowing computers to recognize and process objects in images and video in the same way humans do. The main driving force behind the development of computer vision is the massive amount of data generated in daily life and computer vision helps to process it more efficiently and faster. Object detection accuracy has improved as new computer vision hardware and algorithms have been introduced.

Emotional AI, also known as affective computing or artificial emotional intelligence, is a subset of AI (a broad term for machines that mimic the way humans think) that measures understanding, simulates and responds to human emotions. . It is commonly used in mobile applications, such as Snapchat and Instagram filters for entertainment and fun, which is driving the growth of Emotion AI, which is also used for facial recognition in high-level security devices.

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Companies profiled in the global market report include NVIDIA Corporation, Intel Corporation, Microsoft., IBM, Qualcomm Technologies, Inc., Amazon Web Service, Inc., Advanced Micro Device, Inc. Google, AlphaTechsys, and Hailo.

Some highlights of the report

  • In April 2021, NVIDIA created a new type of NVIDIA-certified system that provides AI to enterprises that run their applications on standard enterprise data center infrastructure. This new category includes high-volume enterprise servers from leading manufacturers that are certified for VMware vSphere 7, the world’s most widely used computing virtualization technology, and can run the NVIDIA AI Enterprise software suite.
  • Software segment accounted for the largest share of revenue in 2021 due to technological advancement and owing to its low cost and strong network infrastructure in developed countries, software system is witnessing increased demand. Manufacturing companies across the globe are planning to switch to AI to reduce costs and eliminate the need for human intervention in various processes, which will drive the revenue growth of the segment.
  • The supervised learning segment accounted for the largest share of revenue in 2021. Supervised learning models can be a valuable solution for eliminating manual classification work and making future predictions based on labeled data. As a result, the demand for supervised learning is increasing day by day.
  • The non-industrial segment accounted for the largest share of revenue in 2021. Advanced technologies are used to make daily life more comfortable and AI in computer vision plays an important role in achieving this. Some applications of non-industrial AI in computer vision are driverless cars, autonomous agricultural equipment, drone applications, intelligent traffic systems, and guided surgery, among others. The demand for such applications is increasing rapidly, driving the revenue growth of this segment.
  • The automotive segment accounted for the largest share of revenue in 2021. During automotive production, computer vision is used to inspect every detail. It detects the defects of each product and rejects those that are defective. This helps ensure that each product is of the highest quality and helps reduce overall costs in the industry, which drives revenue growth for this segment.
  • The North America market accounted for the largest revenue share in 2021, primarily due to the implementation of advanced technologies in the manufacturing and automotive industries. Rising usage of IoT-enabled devices and growing demand for connected devices and wireless connectivity, along with government initiatives to encourage the adoption of computer vision, propelled the growth of the market in North America .


For the purpose of this report, Reports and Data has segmented the AI ​​in Computer Vision market based on component, machine learning model, application, end-use, and region:

Components Outlook (Revenue, USD Billion; 2019-2030)


Machine Learning Model Outlook (Revenue, USD Billion; 2019-2030)

  • Supervised teaching
  • Unsupervised learning
  • Reinforcement learning


Application
Outlook (Revenue, USD billion; 2019-2030)

  • Non-industrial
  • Industrial


End-Use Outlook (Revenue, USD Billion; 2019-2030)

  • Automotive
  • Consumer electronics
  • Detail
  • Security Monitoring
  • Manufacturing


Regional Outlook (Revenue, USD Billion; 2019-2030)

  • North America
  • Europe
  • Asia Pacific
  • Latin America
  • Middle East and Africa


Key Benefits of Artificial Intelligence (AI) in Computer Vision Report:

  • Identification and analysis of market size and competition
  • Qualitative and quantitative analysis of market data
  • Data validated by industry experts after extensive primary and secondary research
  • In-depth regional analysis of the Artificial Intelligence (AI) in Computer Vision industry
  • Profiling of key players with their company overview, business strategies, agreements and partnerships, and product portfolio
  • SWOT and Porter’s Five Forces analysis for an in-depth understanding of the competitive landscape
  • Feasibility analysis and investment analysis to enable strategic investment decisions
  • Analysis of opportunities, drivers, constraints, challenges, risks and limitations


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