세계의 컴퓨터 비전용 AI 시장 : 컴포넌트 유형별, 기능별, 머신러닝 모델별, 전개별, 용도 분야별, 제품별, 최종 사용자별, 기업 규모별, 주요 지역별, 산업 동향 및 예측(-2035년)
AI in Computer Vision Market Till 2035; Distribution by Type of Component, Function, Machine Learning Models, Deployment, Areas of Application, Product, End Users, Company Size, and Key Geographical Regions: Industry Trends and Global Forecasts
상품코드:1787832
리서치사:Roots Analysis
발행일:On Demand Report
페이지 정보:영문 178 Pages
라이선스 & 가격 (부가세 별도)
한글목차
컴퓨터 비전용 AI 시장 개요
세계의 컴퓨터 비전용 AI 시장 규모는 현재 265억 5,000만 달러에서 2035년까지 4,739억 8,000만 달러에 이를 것으로 예측되며, 2035년까지 예측 기간에 CAGR 29.95%로 성장이 예상됩니다.
컴퓨터 비전용 AI 시장 : 성장 및 동향
세계적인 디지털 전환의 진행에 의해 다양한 산업에서 AI의 채용이 진행되고 있습니다. 특히 AI는 컴퓨터 비전 시스템에 필수적이며, 컴퓨터 및 기타 시스템이 디지털 이미지, 동영상 및 다양한 시각 입력에서 중요한 정보를 추출하여 획득한 데이터를 기반으로 행동 및 참조할 수 있도록 합니다. 컴퓨터 비전 기술은 AI와 머신러닝 기술에 크게 의존합니다. 이 분야는 시각 정보와 관련된 다양한 프로세스와 표현의 자동화 및 통합에 중점을 둡니다. 영상 처리(영상 인코딩, 변환, 전송 포함) 및 통계 패턴 분류와 같은 다양한 기술을 포함합니다.
자동차 용도에서 컴퓨터 비전 시스템에 대한 요구 증가, 감정 인식 AI에 대한 관심 증가, 품질 검사 및 자동화에 대한 수요 증가가 AI 비전 기술 시장의 확대를 뒷받침하고 있는 것은 특필할 만합니다. 또한, 비전 시스템 내에서 AI 기술의 진보를 촉진하기 위한 정부의 적극적인 노력은 컴퓨터 비전용 AI에 더 많은 기회를 창출하고 있습니다. 위의 요인으로부터 세계의 컴퓨터 비전용 AI 시장은 예측 기간에 안정된 페이스로 증대할 전망입니다.
이 보고서는 세계의 컴퓨터 비전용 AI 시장에 대한 조사 분석을 통해 시장 규모 추계 및 기회 분석, 경쟁 구도, 기업 프로파일, 메가 트렌드 등의 정보를 제공합니다.
목차
섹션 1 보고서 개요
제1장 서문
제2장 조사 방법
제3장 시장 역학
제4장 거시경제지표
섹션 2 질적 지식
제5장 주요 요약
제6장 서문
제7장 규제 시나리오
섹션 3 시장 개요
제8장 주요 기업의 종합적인 데이터베이스
제9장 경쟁 구도
제10장 화이트 스페이스 분석
제11장 기업의 경쟁력 분석
제12장 컴퓨터 비전용 AI 시장의 스타트업 에코시스템
섹션 4 기업 프로파일
제13장 기업 프로파일
장의 개요
Alphabet
Advanced Micro Devices
Amazon Web Services
Apple
Baumer Optronic
Basler
Baidu
Cognex
CEVA
Facebook
General Electric
Honeywell
Huawei
IBM
Intel
JAI A/S
KEYENCE
Matterport
섹션 5 시장 동향
제14장 메가트렌드 분석
제15장 언멧 요구의 분석
제16장 특허 분석
제17장 최근의 발전
섹션 6 시장 기회 분석
제18장 세계의 컴퓨터 비전용 AI 시장
제19장 시장 기회 : 컴포넌트 유형별
제20장 시장 기회 : 기능 유형별
제21장 시장 기회 : 머신러닝 모델 유형별
제22장 시장 기회 : 전개 유형별
제23장 시장 기회 : 용도 분야별
제24장 시장 기회 : 제품 유형별
제25장 시장 기회 : 최종 사용자 유형별
제26장 북미의 컴퓨터 비전용 AI 시장 기회
제27장 유럽의 컴퓨터 비전용 AI 시장 기회
제28장 아시아의 컴퓨터 비전용 AI 시장 기회
제29장 중동 및 북아프리카(MENA)의 컴퓨터 비전용 AI 시장 기회
제30장 라틴아메리카의 컴퓨터 비전용 AI 시장 기회
제31장 기타 지역의 컴퓨터 비전용 AI 시장 기회
제32장 시장 집중 분석 : 주요 기업별
제33장 인접 시장 분석
섹션 7 전략 도구
제34장 승리의 열쇠가 되는 전략
제35장 Porter's Five Forces 분석
제36장 SWOT 분석
제37장 밸류체인 분석
제38장 Roots의 전략적 제안
섹션 8 기타 독점적 발견
제39장 1차 조사로부터의 지견
제40장 보고서 결론
섹션 9 부록
AJY
영문 목차
영문목차
AI in Computer Vision Market Overview
As per Roots Analysis, the global AI in computer vision market size is estimated to grow from USD 26.55 billion in current year to USD 473.98 billion by 2035, at a CAGR of 29.95% during the forecast period, till 2035.
The opportunity for AI in computer vision market has been distributed across the following segments:
Type of Component
Hardware
Software
Service
Type of Function
Training
Interference
Type of Machine Learning Models
Supervised Learning
Unsupervised Learning
Type of Deployment
Cloud-Based
On-Premises
Areas of Application
Facial Recognition
Image Classification
Object Detection
Object Tracking
Others
Type of Product
PC-Based Computer Vision System
Smart Camera-Based Computer Vision System
Type of End Users
Automotive
Consumer Electronics
Healthcare
Manufacturing
Retail
Security & Surveillance
Sports & Entertainment
Others
Company Size
Large Enterprises
Small and Medium Enterprises
Type of Business Model
B2B
B2C
B2B2C
Geographical Regions
North America
US
Canada
Mexico
Other North American countries
Europe
Austria
Belgium
Denmark
France
Germany
Ireland
Italy
Netherlands
Norway
Russia
Spain
Sweden
Switzerland
UK
Other European countries
Asia
China
India
Japan
Singapore
South Korea
Other Asian countries
Latin America
Brazil
Chile
Colombia
Venezuela
Other Latin American countries
Middle East and North Africa
Egypt
Iran
Iraq
Israel
Kuwait
Saudi Arabia
UAE
Other MENA countries
Rest of the World
Australia
New Zealand
Other countries
AI IN COMPUTER VISION MARKET: GROWTH AND TRENDS
Due to the ongoing global digital transformation, a variety of industries are adopting artificial intelligence (AI). Notably, AI is integral to computer vision systems, which allow computers and other systems to extract significant information from digital images, videos, and various visual inputs, enabling them to act or reference based on the obtained data. Computer vision technology heavily relies on artificial intelligence and machine learning methodologies. This field focuses on automating and integrating diverse processes and representations related to visual information. It encompasses various techniques such as image processing (including encoding, transforming, and transmitting images) and statistical pattern classification.
It is worth mentioning that an increased need for computer vision systems in automotive applications, a growing interest in emotion AI, and a heightened demand for quality inspection and automation, are propelling market expansion for AI vision technology. Further, active government initiatives aimed at promoting advancements in AI technology within vision systems are creating additional opportunities for the AI in computer vision sector. Owing to the abovementioned factors, the global AI in computer vision market is expected to increase at a steady pace during the forecast period.
AI IN COMPUTER VISION MARKET: KEY SEGMENTS
Market Share by Type of Component
Based on type of component, the global AI in computer vision market is segmented into hardware, software, and services. According to our estimates, currently, the software segment captures the majority share of the market. This can be attributed to the vital role of software in supplying essential tools for analyzing and visualizing data.
The software offers various applications, including AI frameworks, AI algorithms, video processing, and more, which further contributes to its market growth. However, the hardware segment is anticipated to grow at a relatively higher CAGR during the forecast period, owing to its crucial role in for data capture in computer vision applications.
Market Share by Type of Function
Based on type of function, the AI in computer vision market is segmented into training and interference. According to our estimates, currently, the training segment captures the majority of the market. This can be attributed to the growing need for training data and advancements in deep learning algorithms, which require targeted training to improve results.
Market Share by Type of Machine Learning Models
Based on type of machine learning models, the AI in computer vision market is segmented into supervised learning and unsupervised learning. According to our estimates, currently, the supervised learning segment captures the majority share of the market. This can be attributed to the model's efficiency in functions such as image classification and object detection, which typically require labeled datasets for training.
However, the unsupervised learning model is anticipated to grow at a relatively higher CAGR during the forecast period. This growth is likely due to its capacity to analyze and interpret data without relying on labeled inputs, making it especially useful in scenarios where obtaining labeled data poses challenges.
Market Share by Type of Deployment
Based on type of deployment, the AI in computer vision market is segmented into cloud-based and on-premises. According to our estimates, currently, the on-premises segment captures the majority share of the market. This can be attributed to its accessibility, flexibility, scalability, and cost-effectiveness provided by AI in computer vision systems. The growing emphasis on accessibility and efficiency by numerous companies is also driving the growth of this segment.
Market Share by Area of Application
Based on areas of application, the AI in computer vision market is segmented into facial recognition, image classification, object detection, object tracking and others. According to our estimates, currently, facial recognition segment captures the majority share of the market. This can be attributed to the fact that facial recognition is an effective tool for security and surveillance, as it can accurately identify individuals. Further, it can aid in locating missing individuals and apprehending criminals by comparing faces in video recordings and databases of known offenders and missing persons.
However, the object detection segment is anticipated to grow at a relatively higher CAGR during the forecast period, due to its essential function in security systems, facilitating real-time image analysis and the identification of intruders, suspicious items, and possible threats.
Market Share by Type of Product
Based on type of product, the AI in computer vision market is segmented into PC-based computer vision system, smart camera-based computer vision system. According to our estimates, currently, the smart camera-based computer vision system captures the majority share of the market. This can be attributed to its extensive use across various sectors such as security, automotive, and healthcare. Additionally, this segment gains from advancements in camera module technology and the integration of AI.
However, PC-based computer vision system is anticipated to grow at a relatively higher CAGR during the forecast period, owing to the rising demand for robust computing solutions capable of managing intricate algorithms and substantial datasets.
Market Share by Type of End-Users
Based on type of end-users, the AI in computer vision market is segmented into automotive, consumer electronics, healthcare, manufacturing, retail, security & surveillance, sports & entertainment and others. According to our estimates, currently, the manufacturing segment captures the majority share of the market.
This can be attributed to the rapid expansion the manufacturing industry is witnessing in the realm of AI-powered computer vision, resulting in the transformation of various processes and delivering significant advantages. Vision computing systems within manufacturing aid in product inspections with accuracy, identifying defects like scratches or cracks. They also contribute to image analysis and the anticipation of possible failures.
However, the healthcare sector is anticipated to grow at a relatively higher CAGR during the forecast period, owing to a range of benefits these systems offer to improve patient care and medical practices.
Market Share by Company Size
Based on company size, the AI in computer vision market is segmented into large and small and medium enterprise. According to our estimates, currently, large enterprise segment captures the majority share of the market. However, the small enterprise segment is anticipated to grow at a relatively higher CAGR during the forecast period.
This is attributed to their flexibility, innovative approaches, concentration on specialized markets, and capacity to adjust to evolving customer preferences and market dynamics.
Market Share by Geographical Regions
Based on geographical regions, the AI in computer vision market is segmented into North America, Europe, Asia, Latin America, Middle East and North Africa, and the rest of the world. According to our estimates, currently, Asia Pacific captures the majority share of the market. This can be attributed to the deployments of the internet of things (IoT) in the area. Further, the strong IT and telecom infrastructure in the region, along with the high number of cloud and edge deployments, are additional factors driving the growth of computer vision systems.
Example Players in AI in Computer Vision Market
Airtel
AT&T
China Mobile
China Unicorn
Ciena
Deepsig
Deutsche Telekom
Ericsson
HPE
Jio
KDDI
KT
Media Tek
National Instruments
NTT DoCoMo
Orange
Qualcomm Technology
Rakuten Mobile
Singtel
SK Telecom
Telefonica
T-Mobile
Verizon
Vodafone
AI IN COMPUTER VISION MARKET: RESEARCH COVERAGE
The report on the AI in computer vision market features insights on various sections, including:
Market Sizing and Opportunity Analysis: An in-depth analysis of the AI in computer vision market, focusing on key market segments, including [A] type of component, [B] type of function, [C] type of machine learning models, [D] type of deployment, [E] areas of application, [F] type of product, [G] type of end users, [H] company size, and [I] key geographical regions.
Competitive Landscape: A comprehensive analysis of the companies engaged in the AI in computer vision market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters and [D] ownership structure.
Company Profiles: Elaborate profiles of prominent players engaged in the AI in computer vision market, providing details on [A] location of headquarters, [B]company size, [C] company mission, [D] company footprint, [E] management team, [F] contact details, [G] financial information, [H] operating business segments, [I] AI in computer vision portfolio, [J] moat analysis, [K] recent developments, and an informed future outlook.
Megatrends: An evaluation of ongoing megatrends in AI in computer vision industry.
Patent Analysis: An insightful analysis of patents filed / granted in the AI in computer vision domain, based on relevant parameters, including [A] type of patent, [B] patent publication year, [C] patent age and [D] leading players.
Recent Developments: An overview of the recent developments made in the AI in computer vision market, along with analysis based on relevant parameters, including [A] year of initiative, [B] type of initiative, [C] geographical distribution and [D] most active players.
Porter's Five Forces Analysis: An analysis of five competitive forces prevailing in the AI in computer vision market, including threats of new entrants, bargaining power of buyers, bargaining power of suppliers, threats of substitute products and rivalry among existing competitors.
SWOT Analysis: An insightful SWOT framework, highlighting the strengths, weaknesses, opportunities and threats in the domain. Additionally, it provides Harvey ball analysis, highlighting the relative impact of each SWOT parameter.
Value Chain Analysis: A comprehensive analysis of the value chain, providing information on the different phases and stakeholders involved in the AI in computer vision market.
KEY QUESTIONS ANSWERED IN THIS REPORT
How many companies are currently engaged in AI in computer vision market?
Which are the leading companies in this market?
What factors are likely to influence the evolution of this market?
What is the current and future market size?
What is the CAGR of this market?
How is the current and future market opportunity likely to be distributed across key market segments?
REASONS TO BUY THIS REPORT
The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. By analyzing the competitive landscape, businesses can make informed decisions to optimize their market positioning and develop effective go-to-market strategies.
The report offers stakeholders a comprehensive overview of the market, including key drivers, barriers, opportunities, and challenges. This information empowers stakeholders to stay abreast of market trends and make data-driven decisions to capitalize on growth prospects.
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TABLE OF CONTENTS
SECTION I: REPORT OVERVIEW
1. PREFACE
1.1. Introduction
1.2. Market Share Insights
1.3. Key Market Insights
1.4. Report Coverage
1.5. Key Questions Answered
1.6. Chapter Outlines
2. RESEARCH METHODOLOGY
2.1. Chapter Overview
2.2. Research Assumptions
2.3. Database Building
2.3.1. Data Collection
2.3.2. Data Validation
2.3.3. Data Analysis
2.4. Project Methodology
2.4.1. Secondary Research
2.4.1.1. Annual Reports
2.4.1.2. Academic Research Papers
2.4.1.3. Company Websites
2.4.1.4. Investor Presentations
2.4.1.5. Regulatory Filings
2.4.1.6. White Papers
2.4.1.7. Industry Publications
2.4.1.8. Conferences and Seminars
2.4.1.9. Government Portals
2.4.1.10. Media and Press Releases
2.4.1.11. Newsletters
2.4.1.12. Industry Databases
2.4.1.13. Roots Proprietary Databases
2.4.1.14. Paid Databases and Sources
2.4.1.15. Social Media Portals
2.4.1.16. Other Secondary Sources
2.4.2. Primary Research
2.4.2.1. Introduction
2.4.2.2. Types
2.4.2.2.1. Qualitative
2.4.2.2.2. Quantitative
2.4.2.3. Advantages
2.4.2.4. Techniques
2.4.2.4.1. Interviews
2.4.2.4.2. Surveys
2.4.2.4.3. Focus Groups
2.4.2.4.4. Observational Research
2.4.2.4.5. Social Media Interactions
2.4.2.5. Stakeholders
2.4.2.5.1. Company Executives (CXOs)
2.4.2.5.2. Board of Directors
2.4.2.5.3. Company Presidents and Vice Presidents
2.4.2.5.4. Key Opinion Leaders
2.4.2.5.5. Research and Development Heads
2.4.2.5.6. Technical Experts
2.4.2.5.7. Subject Matter Experts
2.4.2.5.8. Scientists
2.4.2.5.9. Doctors and Other Healthcare Providers
2.4.2.6. Ethics and Integrity
2.4.2.6.1. Research Ethics
2.4.2.6.2. Data Integrity
2.4.3. Analytical Tools and Databases
3. MARKET DYNAMICS
3.1. Forecast Methodology
3.1.1. Top-Down Approach
3.1.2. Bottom-Up Approach
3.1.3. Hybrid Approach
3.2. Market Assessment Framework
3.2.1. Total Addressable Market (TAM)
3.2.2. Serviceable Addressable Market (SAM)
3.2.3. Serviceable Obtainable Market (SOM)
3.2.4. Currently Acquired Market (CAM)
3.3. Forecasting Tools and Techniques
3.3.1. Qualitative Forecasting
3.3.2. Correlation
3.3.3. Regression
3.3.4. Time Series Analysis
3.3.5. Extrapolation
3.3.6. Convergence
3.3.7. Forecast Error Analysis
3.3.8. Data Visualization
3.3.9. Scenario Planning
3.3.10. Sensitivity Analysis
3.4. Key Considerations
3.4.1. Demographics
3.4.2. Market Access
3.4.3. Reimbursement Scenarios
3.4.4. Industry Consolidation
3.5. Robust Quality Control
3.6. Key Market Segmentations
3.7. Limitations
4. MACRO-ECONOMIC INDICATORS
4.1. Chapter Overview
4.2. Market Dynamics
4.2.1. Time Period
4.2.1.1. Historical Trends
4.2.1.2. Current and Forecasted Estimates
4.2.2. Currency Coverage
4.2.2.1. Overview of Major Currencies Affecting the Market
4.2.2.2. Impact of Currency Fluctuations on the Industry
4.2.3. Foreign Exchange Impact
4.2.3.1. Evaluation of Foreign Exchange Rates and Their Impact on Market
4.2.3.2. Strategies for Mitigating Foreign Exchange Risk
4.2.4. Recession
4.2.4.1. Historical Analysis of Past Recessions and Lessons Learnt
4.2.4.2. Assessment of Current Economic Conditions and Potential Impact on the Market
4.2.5. Inflation
4.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
4.2.5.2. Potential Impact of Inflation on the Market Evolution
4.2.6. Interest Rates
4.2.6.1. Overview of Interest Rates and Their Impact on the Market
4.2.6.2. Strategies for Managing Interest Rate Risk
4.2.7. Commodity Flow Analysis
4.2.7.1. Type of Commodity
4.2.7.2. Origins and Destinations
4.2.7.3. Values and Weights
4.2.7.4. Modes of Transportation
4.2.8. Global Trade Dynamics
4.2.8.1. Import Scenario
4.2.8.2. Export Scenario
4.2.9. War Impact Analysis
4.2.9.1. Russian-Ukraine War
4.2.9.2. Israel-Hamas War
4.2.10. COVID Impact / Related Factors
4.2.10.1. Global Economic Impact
4.2.10.2. Industry-specific Impact
4.2.10.3. Government Response and Stimulus Measures
4.2.10.4. Future Outlook and Adaptation Strategies
4.2.11. Other Indicators
4.2.11.1. Fiscal Policy
4.2.11.2. Consumer Spending
4.2.11.3. Gross Domestic Product (GDP)
4.2.11.4. Employment
4.2.11.5. Taxes
4.2.11.6. R&D Innovation
4.2.11.7. Stock Market Performance
4.2.11.8. Supply Chain
4.2.11.9. Cross-Border Dynamics
SECTION II: QUALITATIVE INSIGHTS
5. EXECUTIVE SUMMARY
6. INTRODUCTION
6.1. Chapter Overview
6.2. Overview of AI in Computer Vision Market
6.2.1. Type of Component
6.2.2. Type of Function
6.2.3. Type of Machine Learning Models
6.2.4. Type of Deployment
6.2.5. Areas of Application
6.2.6. Type of Product
6.2.7. Type of End Users
6.3. Future Perspective
7. REGULATORY SCENARIO
SECTION III: MARKET OVERVIEW
8. COMPREHENSIVE DATABASE OF LEADING PLAYERS
9. COMPETITIVE LANDSCAPE
9.1. Chapter Overview
9.2. Motion Control: Overall Market Landscape
9.2.1. Analysis by Year of Establishment
9.2.2. Analysis by Company Size
9.2.3. Analysis by Location of Headquarters
9.2.4. Analysis by Ownership Structure
10. WHITE SPACE ANALYSIS
11. COMPANY COMPETITIVENESS ANALYSIS
12. STARTUP ECOSYSTEM IN THE AI IN COMPUTER VISION MARKET
12.1. AI in Computer Vision Market: Market Landscape of Startups
12.1.1. Analysis by Year of Establishment
12.1.2. Analysis by Company Size
12.1.3. Analysis by Company Size and Year of Establishment
12.1.4. Analysis by Location of Headquarters
12.1.5. Analysis by Company Size and Location of Headquarters
12.1.6. Analysis by Ownership Structure
12.2. Key Findings
SECTION IV: COMPANY PROFILES
13. COMPANY PROFILES
13.1. Chapter Overview
13.2. Alphabet*
13.2.1. Company Overview
13.2.2. Company Mission
13.2.3. Company Footprint
13.2.4. Management Team
13.2.5. Contact Details
13.2.6. Financial Performance
13.2.7. Operating Business Segments
13.2.8. Service / Product Portfolio (project specific)
13.2.9. MOAT Analysis
13.2.10. Recent Developments and Future Outlook
13.3. Advanced Micro Devices
13.4. Amazon Web Services
13.5. Apple
13.6. Baumer Optronic
13.7. Basler
13.8. Baidu
13.9. Cognex
13.10. CEVA
13.11. Facebook
13.12. General Electric
13.13. Honeywell
13.14. Huawei
13.15. IBM
13.16. Intel
13.17. JAI A/S
13.18. KEYENCE
13.19. Matterport
SECTION V: MARKET TRENDS
14. MEGA TRENDS ANALYSIS
15. UNMEET NEED ANALYSIS
16. PATENT ANALYSIS
17. RECENT DEVELOPMENTS
17.1. Chapter Overview
17.2. Recent Funding
17.3. Recent Partnerships
17.4. Other Recent Initiatives
SECTION VI: MARKET OPPORTUNITY ANALYSIS
18. GLOBAL AI IN COMPUTER VISION MARKET
18.1. Chapter Overview
18.2. Key Assumptions and Methodology
18.3. Trends Disruption Impacting Market
18.4. Demand Side Trends
18.5. Supply Side Trends
18.6. Global AI in Computer Vision Market, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
18.7. Multivariate Scenario Analysis
18.7.1. Conservative Scenario
18.7.2. Optimistic Scenario
18.8. Investment Feasibility Index
18.9. Key Market Segmentations
19. MARKET OPPORTUNITIES BASED ON TYPE OF COMPONENT
19.1. Chapter Overview
19.2. Key Assumptions and Methodology
19.3. Revenue Shift Analysis
19.4. Market Movement Analysis
19.5. Penetration-Growth (P-G) Matrix
19.6. AI in Computer Vision Market for Hardware: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
19.7. AI in Computer Vision Market for Software: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
19.8. Data Triangulation and Validation
19.8.1. Secondary Sources
19.8.2. Primary Sources
19.8.3. Statistical Modeling
20. MARKET OPPORTUNITIES BASED ON TYPE OF FUNCTION
20.1. Chapter Overview
20.2. Key Assumptions and Methodology
20.3. Revenue Shift Analysis
20.4. Market Movement Analysis
20.5. Penetration-Growth (P-G) Matrix
20.6. AI in Computer Vision Market for Training: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
20.7. AI in Computer Vision Market for Interference: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
20.8. Data Triangulation and Validation
20.8.1. Secondary Sources
20.8.2. Primary Sources
20.8.3. Statistical Modeling
21. MARKET OPPORTUNITIES BASED ON TYPE OF MACHINE LEARNING MODELS
21.1. Chapter Overview
21.2. Key Assumptions and Methodology
21.3. Revenue Shift Analysis
21.4. Market Movement Analysis
21.5. Penetration-Growth (P-G) Matrix
21.6. AI in Computer Vision Market for Supervised Learning: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
21.7. AI in Computer Vision Market for Unsupervised Learning: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
21.8. Data Triangulation and Validation
21.8.1. Secondary Sources
21.8.2. Primary Sources
21.8.3. Statistical Modeling
22. MARKET OPPORTUNITIES BASED ON TYPE OF DEPLOYMENT
22.1. Chapter Overview
22.2. Key Assumptions and Methodology
22.3. Revenue Shift Analysis
22.4. Market Movement Analysis
22.5. Penetration-Growth (P-G) Matrix
22.6. AI in Computer Vision Market for Cloud-Based: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
22.7. AI in Computer Vision Market for On-Premises: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
22.8. Data Triangulation and Validation
22.8.1. Secondary Sources
22.8.2. Primary Sources
22.8.3. Statistical Modeling
23. MARKET OPPORTUNITIES BASED ON AREAS OF APPLICATIONS
23.1. Chapter Overview
23.2. Key Assumptions and Methodology
23.3. Revenue Shift Analysis
23.4. Market Movement Analysis
23.5. Penetration-Growth (P-G) Matrix
23.6. AI in Computer Vision Market for Facial Recognition: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
23.7. AI in Computer Vision Market for Image Classification: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
23.8. AI in Computer Vision Market for Object Detection: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
23.9. AI in Computer Vision Market for Object Tracking: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
23.10. AI in Computer Vision Market for Others: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
23.11. Data Triangulation and Validation
23.11.1. Secondary Sources
23.11.2. Primary Sources
23.11.3. Statistical Modeling
24. MARKET OPPORTUNITIES BASED ON TYPE OF PRODUCT
24.1. Chapter Overview
24.2. Key Assumptions and Methodology
24.3. Revenue Shift Analysis
24.4. Market Movement Analysis
24.5. Penetration-Growth (P-G) Matrix
24.6. AI in Computer Vision Market for PC-Based Computer Vision System: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
24.7. AI in Computer Vision Market for Smart Camera-Based Computer Vision System: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
24.8. Data Triangulation and Validation
24.8.1. Secondary Sources
24.8.2. Primary Sources
24.8.3. Statistical Modeling
25. MARKET OPPORTUNITIES BASED ON TYPE OF END-USERS
25.1. Chapter Overview
25.2. Key Assumptions and Methodology
25.3. Revenue Shift Analysis
25.4. Market Movement Analysis
25.5. Penetration-Growth (P-G) Matrix
25.6. AI in Computer Vision Market for Automotive: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
25.7. AI in Computer Vision Market for Consumer Electronics: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
25.8. AI in Computer Vision Market for Healthcare: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
25.9. AI in Computer Vision Market for Manufacturing: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
25.10. AI in Computer Vision Market for Retail: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
25.11. AI in Computer Vision Market for Security & Surveillance: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
25.12. AI in Computer Vision Market for Sports & Entertainment: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
25.13. AI in Computer Vision Market for Others: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
25.14. Data Triangulation and Validation
25.14.1. Secondary Sources
25.14.2. Primary Sources
25.14.3. Statistical Modeling
26. MARKET OPPORTUNITIES FOR AI IN COMPUTER VISION IN NORTH AMERICA
26.1. Chapter Overview
26.2. Key Assumptions and Methodology
26.3. Revenue Shift Analysis
26.4. Market Movement Analysis
26.5. Penetration-Growth (P-G) Matrix
26.6. AI in Computer Vision Market in North America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
26.6.1. AI in Computer Vision Market in the US: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
26.6.2. AI in Computer Vision Market in Canada: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
26.6.3. AI in Computer Vision Market in Mexico: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
26.6.4. AI in Computer Vision Market in Other North American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
26.7. Data Triangulation and Validation
27. MARKET OPPORTUNITIES FOR AI IN COMPUTER VISION IN EUROPE
27.1. Chapter Overview
27.2. Key Assumptions and Methodology
27.3. Revenue Shift Analysis
27.4. Market Movement Analysis
27.5. Penetration-Growth (P-G) Matrix
27.6. AI in Computer Vision Market in Europe: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.1. AI in Computer Vision Market in Austria: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.2. AI in Computer Vision Market in Belgium: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.3. AI in Computer Vision Market in Denmark: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.4. AI in Computer Vision Market in France: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.5. AI in Computer Vision Market in Germany: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.6. AI in Computer Vision Market in Ireland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.7. AI in Computer Vision Market in Italy: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.8. AI in Computer Vision Market in Netherlands: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.9. AI in Computer Vision Market in Norway: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.10. AI in Computer Vision Market in Russia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.11. AI in Computer Vision Market in Spain: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.12. AI in Computer Vision Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.13. AI in Computer Vision Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.14. AI in Computer Vision Market in Switzerland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.15. AI in Computer Vision Market in the UK: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.6.16. AI in Computer Vision Market in Other European Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
27.7. Data Triangulation and Validation
28. MARKET OPPORTUNITIES FOR AI IN COMPUTER VISION IN ASIA
28.1. Chapter Overview
28.2. Key Assumptions and Methodology
28.3. Revenue Shift Analysis
28.4. Market Movement Analysis
28.5. Penetration-Growth (P-G) Matrix
28.6. AI in Computer Vision Market in Asia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
28.6.1. AI in Computer Vision Market in China: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
28.6.2. AI in Computer Vision Market in India: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
28.6.3. AI in Computer Vision Market in Japan: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
28.6.4. AI in Computer Vision Market in Singapore: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
28.6.5. AI in Computer Vision Market in South Korea: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
28.6.6. AI in Computer Vision Market in Other Asian Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
28.7. Data Triangulation and Validation
29. MARKET OPPORTUNITIES FOR AI IN COMPUTER VISION IN MIDDLE EAST AND NORTH AFRICA (MENA)
29.1. Chapter Overview
29.2. Key Assumptions and Methodology
29.3. Revenue Shift Analysis
29.4. Market Movement Analysis
29.5. Penetration-Growth (P-G) Matrix
29.6. AI in Computer Vision Market in Middle East and North Africa (MENA): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
29.6.1. AI in Computer Vision Market in Egypt: Historical Trends (Since 2019) and Forecasted Estimates (Till 205)
29.6.2. AI in Computer Vision Market in Iran: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
29.6.3. AI in Computer Vision Market in Iraq: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
29.6.4. AI in Computer Vision Market in Israel: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
29.6.5. AI in Computer Vision Market in Kuwait: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
29.6.6. AI in Computer Vision Market in Saudi Arabia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
29.6.7. AI in Computer Vision Market in United Arab Emirates (UAE): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
29.6.8. AI in Computer Vision Market in Other MENA Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
29.7. Data Triangulation and Validation
30. MARKET OPPORTUNITIES FOR AI IN COMPUTER VISION IN LATIN AMERICA
30.1. Chapter Overview
30.2. Key Assumptions and Methodology
30.3. Revenue Shift Analysis
30.4. Market Movement Analysis
30.5. Penetration-Growth (P-G) Matrix
30.6. AI in Computer Vision Market in Latin America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
30.6.1. AI in Computer Vision Market in Argentina: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
30.6.2. AI in Computer Vision Market in Brazil: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
30.6.3. AI in Computer Vision Market in Chile: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
30.6.4. AI in Computer Vision Market in Colombia Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
30.6.5. AI in Computer Vision Market in Venezuela: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
30.6.6. AI in Computer Vision Market in Other Latin American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
30.7. Data Triangulation and Validation
31. MARKET OPPORTUNITIES FOR AI IN COMPUTER VISION IN REST OF THE WORLD
31.1. Chapter Overview
31.2. Key Assumptions and Methodology
31.3. Revenue Shift Analysis
31.4. Market Movement Analysis
31.5. Penetration-Growth (P-G) Matrix
31.6. AI in Computer Vision Market in Rest of the World: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
31.6.1. AI in Computer Vision Market in Australia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
31.6.2. AI in Computer Vision Market in New Zealand: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
31.6.3. AI in Computer Vision Market in Other Countries
31.7. Data Triangulation and Validation
32. MARKET CONCENTRATION ANALYSIS: DISTRIBUTION BY LEADING PLAYERS
