Global Reinforcement Learning in Computer Vision to Reach $34.7 billion by 2027

DUBLIN, Feb. 21, 2022 /PRNewswire/ — The “AI in Computer Vision Market by Technology, Solutions, Use Cases, Deployment Model and Industry Verticals 2022 – 2027” report has been added to’s offering.

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This report assesses the application of AI in computer vision systems used in conjunction with connected devices, hardware components, embedded software, AI platforms, and analytics. The report analyzes machine learning models and APIs used in computer vision systems along with the application of neural networks in AI analytics systems.

This research also evaluates the causal relationship of computer vision systems with IoT, Edge computing, and connected machines along with core hardware and software technology. The report also analyzes the relation of emotion AI with computer vision systems along with the market factors.

Select Report Findings:

  • The global market for AI in computer vision will reach $73.7 billion by 2027

  • Global reinforcement learning in computer vision will reach $34.7 billion by 2027

  • Global 2D and 3D machine vision will reach $3.4 billion and $7.4 billion respectively by 2027

  • Global AI in computer vision by unit volume expansion will grow at 37.8% CAGR through 2027

  • Global market for cameras with greater than 125 frame rate per second will exceed $10 billion by 2027

  • Asia Pacific software market in support of AI in computer vision will reach $11.8 billion by 2027 with 33.7% CAGR

Computer vision systems are dedicated to simulate the human visual system while analyzing the information extracted from photos and videos. They do this by way of mathematical operations in conjunction with signal processing systems to process both digital and analog images. These systems leverage both two dimensional and three-dimensional processes.

AI represents the ability to organize information and create outcomes in learning, decision-making, and problem-solving using a computer-enabled robotic system in the same way a human brain does. The integration of AI and computer vision systems enhance the accuracy of object identification, classification, and analysis of information.

Through leveraging AI, computer vision systems provide a robotic system in which vision sensing capabilities provide information about the environment. One of the best examples of this in practice is autonomous vehicles, which rely on computer vision and AI-based decision making for safe travel.

Key Topics Covered:

1.0 Executive Summary

2.0 Introduction
2.1 Defining AI in Computer Vision
2.2 Artificial General Intelligence and Super Intelligence
2.3 AI and Computer Vision Market Predictions
2.4 AI Outcomes and Enterprise Benefits
2.5 Cognitive Computing and Swarm Intelligence
2.6 Market Driver and Opportunity Analysis
2.7 Market Challenge Analysis
2.8 Covid-19 Impact
2.9 Value Chain Analysis
2.10 Pricing Analysis
2.11 Hs Code 854231
2.12 AI Patent and Regulatory Framework
2.13 AI Public Policy Issues

3.0 Technology and Application Analysis
3.1 Technology Analysis
3.2 IoT Device Ecosystem: Consumer, Enterprise, Industrial, and Government
3.3 Machine Learning Model
3.4 Artificial Neural Networks
3.5 Emotion AI Analysis
3.6 Edge Computing and 5G Networks
3.7 Smart Machine and Virtual Twinning
3.8 Factory Automation and Industry 4.0
3.9 Building Automation and Smart Workplace
3.10 Cloud Robotics

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