AI In Computer Vision Global Market Report 2023: Advancements in Deep Learning and Neural Network Technologies Drive Growth - ResearchAndMarkets.com

Facial recognition technology uses deep learning models to detect, normalize, validate, match, and identify faces.

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Monday, March 13, 2023
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Technology, Artificial Intelligence, Machine learning, CT, Research, Economic development, AI, Industrial, CPU, Hardware, Environment, Intelligence, Consumer electronics, USD, Acquisition, Algorithm, Automotive industry, Center for Security and Emerging Technology, Siemens Healthineers, Science and technology in Asia, Workflow, Security, PROLOG, CSET, Human, Automation, Component, LISP, Amazon Web Services, Region, 3D, RAM, Medical device, Agriculture, Software
Geotags: 
US, GERMANY, CHINA
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RESEARCH AND MARKETS, RESEARCHANDMARKETS.COM
Summary
Key Points: 
  • Facial recognition technology uses deep learning models to detect, normalize, validate, match, and identify faces.
  • The deployment of computer vision systems is rapidly increasing because of the growing need for automation in China.
  • The country has implemented several large-scale surveillance systems that rely on computer vision algorithms to monitor and track individuals in public spaces.
  • Emerging Applications of AI Computer Vision in Agriculture, Logistics, and Manufacturing


The "AI In Computer Vision Market by Component (Hardware, Software), Function (Training, Inference), Application (Industrial, Non-industrial), End-use Industry (Automotive, Consumer Electronics) and Region - Global Forecast to 2028" report has been added to ResearchAndMarkets.com's offering.

The global AI in computer vision market is expected to be valued at USD 17.2 billion in 2023 and is projected to reach USD 45.7 billion by 2028 at a CAGR of 21.5% from 2023 to 2028. The advancement in 3D acquisition systems and the computing power of smart devices/laptops have helped solve identification tasks by fitting a deformable 3D model to 2D images.

Facial recognition technology uses deep learning models to detect, normalize, validate, match, and identify faces. AI models are trained with millions of facial images, and depending on the use case, they are designed to generate mathematical representations of a human face (embeddings). These embeddings can be stored and referenced by other models to infer identity.

AI Solution: The largest growing software segment for AI in the computer vision market

Recently, most developments have been witnessed in AI solutions and related software development kits. AI solutions are created using nonprocedural languages such as LISP and PROLOG. These languages allow systems to learn and modify responses according to the environment. Depending on the application, a fast CPU, high-capacity RAM, large storage capacity, a graphics card, and a few specialized input and output devices are required to install AI software. Companies are trying to provide AI solutions to reduce the volume and complexity of data in various verticals. Digitalizing healthcare and combining the power of artificial intelligence can help healthcare providers remain competitive despite the shortage of skilled staff and continuous increase in the volumes of imaging scans. For instance, AI solutions by Siemens Healthineers (Germany) are helpful in clinical processes. During the scan preparation, AI assists in the form of an intelligent and automated workflow in CT scans to generate reliable and consistent images while reducing unwanted variations.

Consumer Electronics: Largest end-use industry of AI in the computer vision market

The consumer electronics vertical includes cameras, gaming devices, wearables, and smartphones. The addition of AI capabilities to smartphones will help change two main aspects: user-machine interaction and context-personalized openness. User-machine interaction will improve the efficiency between the users and their phones across text, voice, image, video, and sensors. In contrast, context-personalized openness will actively provide services and aggregated information across apps, content, third-party, and native features. Amazon Web Services (US) has launched an AI-powered camera called DeepLens for developing and deploying machine learning algorithms and services for AI-powered transcription and translation. DeepLens includes applications such as optical character recognition and image and object recognition, which would help test and develop new vision-based AI functionalities efficiently and quickly.

China: The largest consumer region in Asia Pacific for AI in computer vision

The deployment of computer vision systems is rapidly increasing because of the growing need for automation in China. Moreover, there is a year-on-year increase in labor costs, so companies are increasingly adopting automation systems to reduce production costs. A rise in manufacturing operations mainly contributes to the country's economic development.

China has invested heavily in computer vision technologies for security and surveillance purposes. The country has implemented several large-scale surveillance systems that rely on computer vision algorithms to monitor and track individuals in public spaces. In January 2022, a new report from the Center for Security and Emerging Technology (CSET) found that the research sector of China is investing heavily in AI-based computer vision technology, especially in the security and surveillance sector. It has a massive lead in three key areas: person re-identification (REID), crowd counting, and spoofing detection.

Market Dynamics

Drivers

  • Increasing Demand for Automation and Efficiency
  • Advancements in Deep Learning and Neural Network Technologies
  • Growing Impact of AI in Machine Vision

Restraints

  • Limited Understanding and Technical Expertise in AI Computer Vision
  • High Cost of Acquiring and Implementing AI Computer Vision Solutions
  • Lack of Skilled Professionals in Manufacturing Factories

Opportunities

  • Emerging Applications of AI Computer Vision in Agriculture, Logistics, and Manufacturing
  • Increasing Use of AI Computer Vision in Autonomous Systems
  • Growing Demand for Real-Time and High-Precision Visual Data Analysis
  • Development of Machine Learning Pertaining to Vision Technology

Challenges

  • Overcoming Limitations in Current AI Computer Vision Technologies
  • Maintaining Trust and Transparency of AI Computer Vision Systems

Key Topics Covered:

1 Introduction

2 Research Methodology

3 Executive Summary

4 Premium Insights

5 Market Overview

6 AI in Computer Vision Market, by Component

6.1 Introduction

6.2 Hardware

6.3 Software

7 AI in Computer Vision Market, by Function

7.1 Introduction

7.2 Training

7.3 Inference

8 Various Machine Learning Models in Computer Vision

8.1 Introduction

8.2 Supervised Learning

8.3 Unsupervised Learning

8.4 Reinforcement Learning

9 AI in Computer Vision Market, by Application

9.1 Introduction

9.2 Non-Industrial

9.3 Industrial

10 AI in Computer Vision Market, by End-Use Industry

10.1 Introduction

10.2 Automotive

10.2.1 Increasing Need to Improve Road Safety and Reduce Mishaps to Drive Use of Computer Vision Solutions

10.2.2 Adas and Infotainment

10.2.3 Autonomous and Semi-Autonomous Vehicles

10.3 Consumer Electronics

10.3.1 Growing Demand for Smartphones with Front and Rear Cameras to Boost Market

10.3.2 Gaming

10.3.3 Cameras

10.3.4 Wearables

10.3.5 Smartphones

10.4 Healthcare

10.4.1 Rising Adoption of AI in Computer Vision Technology in Healthcare Industry to Propel Market

10.4.2 Radiology

10.4.3 Medical Imaging

10.5 Retail

10.6 Security & Surveillance

10.7 Manufacturing

10.8 Agriculture

11 AI in Computer Vision Market, by Region

12 Competitive Landscape

13 Company Profiles

14 Appendix

Companies Mentioned

  • Advanced Micro Devices, Inc.(Amd)
  • Algolux
  • Alphabet, Inc.
  • Amazon.Com, Inc.
  • Amp Robotics
  • Athena Security
  • Basler Ag
  • Creative Virtual
  • Curemetrix
  • Datagen
  • Graphcore
  • Groopic
  • Groq, Inc.
  • Hailo
  • IBM Corporation
  • Intel Corporation
  • Microsoft Corporation
  • Neurala, Inc
  • Nvidia Corporation
  • Qualcomm Technologies, Inc.
  • Robotic Vision Technologies
  • Sighthound, Inc.
  • Snorkel Ai
  • Ultraleap
  • Verta Inc.
  • Vizseek

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

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