한글목차

세계 비주얼 AI 분석 시장의 미래는 스마트 드라이브, 금융 서비스, 의료, 스마트 시티 시장에서의 기회로 인해 유망합니다. 세계 비주얼 AI 분석 시장은 2025년부터 2031년까지 CAGR 24.6%로 성장할 것으로 예측됩니다. 이 시장의 주요 촉진요인은 다양한 산업에서 생성되는 이미지 및 동영상 데이터의 양이 급격히 증가하고, 자동화 및 효율화에 대한 수요가 증가하고, 비주얼 AI 분석과 IoT 기기 및 엣지 컴퓨팅 플랫폼과의 통합이 진행되고 있다는 점입니다.

• Lucintel의 예측에 따르면, 유형별로는 하드웨어가 예측 기간 동안 높은 성장세를 보일 것으로 예상됩니다.
• A 용도별로는 스마트 드라이빙이 가장 큰 부문을 차지할 것으로 보입니다.
• 지역별로는 아시아태평양이 예측 기간 동안 가장 높은 성장세를 보일 것으로 예상됩니다.

비주얼 AI 분석 시장의 전략적 성장 기회

비주얼 AI 분석 시장은 주요 응용 분야에 걸쳐 몇 가지 전략적 성장 기회를 제공합니다. 이러한 기회는 기술 발전과 시각적 분석 솔루션에 대한 수요 증가로 인해 발생합니다.

• 의료 진단 분야에서의 확장 : 의료 진단 분야에서 비주얼 AI의 성장 잠재력은 매우 큽니다. 질병 조기 발견을 위한 첨단 영상 시스템 개발, AI 기반 진단 도구, 원격의료 애플리케이션 등이 그 예입니다. 이러한 솔루션은 진단의 정확성과 효율성을 향상시키고 첨단 의료 기술에 대한 수요 증가에 대응할 수 있습니다.
• 자율주행차 및 스마트 교통수단의 성장 : 자율주행차 시장은 비주얼 AI에 큰 성장 기회를 제공합니다. 내비게이션 시스템 강화, 물체 감지, 충돌 방지 등 다양한 용도로 활용될 수 있습니다. 자율주행차가 대중화됨에 따라 고급 비주얼 AI 솔루션에 대한 수요는 계속 확대될 것이며, 이 분야의 혁신과 발전을 촉진할 것입니다.
• 소매 및 고객 경험 솔루션에 적용 : 비주얼 AI는 자동 계산대 시스템, 개인화된 쇼핑 경험, 재고 관리 등의 기회를 제공함으로써 소매 분야에서 큰 잠재력을 가지고 있습니다. 이러한 솔루션은 소매업을 혁신하고, 고객 참여를 강화하며, 업무 효율성을 향상시키고, 소매 기술 분야의 성장에 기여할 수 있습니다.
• 보안 및 감시 시스템의 발전 : 보안 및 감시 분야는 비주얼 AI의 성장 기회를 제공합니다. 향상된 얼굴 인식, 행동 분석, 자동화된 위협 탐지 등 다양한 응용 분야가 있습니다. 이러한 솔루션은 공공안전 및 보안 조치를 개선하고 고급 비주얼 AI 기술에 대한 수요를 촉진할 것입니다.
• 실시간 분석을 위한 엣지 컴퓨팅과의 통합 : 비주얼 AI를 엣지 컴퓨팅 기술과 통합하면 네트워크 엣지에서 실시간 데이터 처리가 가능해져 성장 기회를 창출할 수 있습니다. 이러한 통합은 자율주행차, 스마트 시티, 원격 모니터링 등 다양한 분야의 애플리케이션을 지원하여 성능 향상과 대기 시간 단축을 실현할 수 있습니다.

이러한 전략적 성장 기회는 비주얼 AI 분석이 혁신을 촉진하고 헬스케어, 교통, 소매, 보안, 엣지 컴퓨팅의 진화하는 요구를 충족시킬 수 있는 잠재력을 보여줍니다. 이러한 분야에 집중함으로써 시장은 기술 발전을 활용하여 성장과 개척을 지원할 수 있습니다.

비주얼 AI 분석 시장의 촉진요인 및 과제

비주얼 AI 분석 시장은 성장과 개척에 영향을 미치는 다양한 촉진요인과 과제에 영향을 받고 있습니다. 이러한 요인을 이해하는 것은 시장을 탐색하고 성공하기 위해 매우 중요합니다.

비주얼 AI 분석 시장의 촉진요인으로는 다음과 같은 것들이 있습니다:

• AI와 머신러닝의 발전 : AI와 머신러닝의 기술적 발전이 비주얼 AI 분석의 성장을 촉진하고 있습니다. 개선된 알고리즘과 신경망은 이미지 및 영상 분석의 정확성과 효율성을 높이고 비주얼 AI 시스템의 기능과 용도를 확장하고 있습니다.
• 실시간 데이터 처리에 대한 수요 증가 : 실시간 데이터 처리에 대한 수요 증가는 비주얼 AI 시장의 주요 촉진요인입니다. 자율주행차, 스마트 시티, 보안 등의 분야에서 빠르고 정확한 시각적 분석이 필요하며, 이는 고급 비주얼 AI 솔루션에 대한 수요를 촉진하고 있습니다.
• 헬스케어 분야에서의 활용 확대 : 의료 영상 및 진단 등 헬스케어 분야에서의 비주얼 AI 활용 확대가 시장 성장의 원동력이 되고 있습니다. 정확하고 효율적인 진단 도구에 대한 요구가 헬스케어 분야에서 AI 기반 시각적 솔루션의 개발 및 채택을 뒷받침하고 있습니다.
• 스마트 시티 및 감시 프로젝트의 성장 : 스마트 시티의 발전과 공공안전 및 감시 분야에 대한 관심이 높아지면서 비주얼 AI 기술에 대한 수요가 증가하고 있습니다. 첨단 영상 분석 및 얼굴 인식 시스템은 도시 환경의 보안과 효율성을 향상시키고 있습니다.
• 엣지 컴퓨팅 기술과의 통합 : 비주얼 AI와 엣지 컴퓨팅 기술의 통합은 엣지에서의 실시간 데이터 처리를 가능하게함으로써 시장 성장을 촉진하고 있습니다. 이러한 추세는 성능을 향상시키고, 대기 시간을 단축하며, 다양한 분야의 다양한 애플리케이션을 지원합니다.

비주얼 AI 분석 시장의 과제는 다음과 같습니다:

• 프라이버시 및 데이터 보안 문제 : 프라이버시 및 데이터 보안은 비주얼 AI 시장에서 중요한 이슈입니다. 기밀 정보를 다루고 규정을 준수하는 것은 신뢰를 유지하고 보안 문제를 해결하는 데 매우 중요합니다.
• 높은 비용과 리소스 요구 사항 : 고급 비주얼 AI 시스템을 개발하고 구현하는 데는 많은 비용과 리소스가 소요됩니다. 기술 및 인프라와 관련된 높은 비용은 특히 소규모 조직에 있어 보급의 장벽이 될 수 있습니다.
• 윤리적, 규제적 문제 : AI 알고리즘의 편향성, 모니터링 기술 사용 등 윤리적, 규제적 문제는 시장에 도전이 될 수 있습니다. 이러한 문제를 해결하는 것은 비주얼 AI의 책임감 있는 사용을 보장하고 규제 준수를 유지하는 데 필수적입니다.

AI 기술의 발전, 실시간 처리에 대한 수요 증가, 헬스케어 및 스마트 시티 애플리케이션의 성장은 비주얼 AI 분석 시장의 주요 촉진요인입니다. 그러나 지속적인 성장과 채택을 뒷받침하기 위해서는 프라이버시, 비용, 윤리적 고려사항과 관련된 문제를 해결해야 합니다. 이러한 촉진요인과 도전 과제의 균형을 맞추는 것이 시장 개척과 성공에 매우 중요합니다.

목차

제1장 주요 요약

제2장 세계의 비주얼 AI 분석 시장 : 시장 역학

• 소개, 배경, 분류
• 공급망
• 업계 성장 촉진요인과 과제

제3장 2019년부터 2031년까지 시장 동향과 예측 분석

• 거시경제 동향(2019-2024년)과 예측(2025-2031년)
• 세계의 비주얼 AI 분석 시장 동향(2019-2024년)과 예측(2025-2031년)
• 유형별 세계의 비주얼 AI 분석 시장
  • 하드웨어
  • 소프트웨어
• 용도별 세계의 비주얼 AI 분석 시장
  • 스마트 드라이빙
  • 금융 서비스
  • 치료
  • 스마트 시티
  • 기타

제4장 2019년부터 2031년까지 지역별 시장 동향과 예측 분석

• 지역별 세계의 비주얼 AI 분석 시장
• 북미의 비주얼 AI 분석 시장
• 유럽의 비주얼 AI 분석 시장
• 아시아태평양의 비주얼 AI 분석 시장
• 기타 지역의 비주얼 AI 분석 시장

제5장 경쟁 분석

• 제품 포트폴리오 분석
• 운영 통합
• Porter's Five Forces 분석

제6장 성장 기회와 전략 분석

• 성장 기회 분석
  • 유형별 세계의 비주얼 AI 분석 시장 성장 기회
  • 용도별 세계의 비주얼 AI 분석 시장 성장 기회
  • 지역별 세계의 비주얼 AI 분석 시장 성장 기회
• 세계의 비주얼 AI 분석 시장 최신 동향
• 전략 분석
  • 신제품 개발
  • 세계의 비주얼 AI 분석 시장 커패시티 확대
  • 세계의 비주얼 AI 분석 시장 합병, 인수, 합작투자
  • 인증과 라이선싱

제7장 주요 기업 개요

• Cambricon
• Clarifai
• CloudSight
• DataRobot
• DeepVisionAI
• EdgeQ
• EyeEM

영문목차

The future of the global visual AI analysis market looks promising with opportunities in the smart driving, financial service, medical treatment, and smart city markets. The global visual AI analysis market is expected to grow with a CAGR of 24.6% from 2025 to 2031. The major drivers for this market are the exponential increase in the volume of image and video data generated across various industries, growing demand for automation and efficiency, as well as, integration of Visual AI analysis with IoT devices and edge computing platforms.

• Lucintel forecasts that, within the type category, hardware is expected to witness higher growth over the forecast period.
• Within the application category, smart driving will remain the largest segment.
• In terms of regions, APAC is expected to witness the highest growth over the forecast period.

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Emerging Trends in the Visual AI Analysis Market

The visual AI analysis market is evolving with several key trends that are shaping its future and expanding its applications. These trends reflect advancements in technology and increasing adoption across different sectors.

• Integration with Edge Computing: Visual AI systems are increasingly being integrated with edge computing technologies. This trend allows for real-time processing of visual data at the edge of the network, reducing latency and improving performance. By processing data locally rather than sending it to a centralized server, edge computing enhances the efficiency and responsiveness of visual AI applications in areas such as autonomous vehicles and smart cameras.
• Advancements in Deep Learning Algorithms: There is a significant focus on improving deep learning algorithms for visual AI. Recent advancements in neural networks and machine learning techniques are enhancing the accuracy and efficiency of image and video analysis. These improvements enable more sophisticated applications such as real-time facial recognition, advanced object detection, and enhanced image quality in various sectors.
• Growing Adoption in Healthcare: Visual AI analysis is seeing increased adoption in the healthcare sector. Innovations include AI-driven medical imaging for diagnostics, such as detecting tumors and analyzing X-rays. This trend is driven by the need for faster and more accurate diagnostic tools, which improve patient outcomes and streamline medical workflows.
• Expansion into Retail and Customer Experience: The retail sector is leveraging visual AI to enhance customer experience and operational efficiency. Applications include AI-powered checkout systems, personalized shopping experiences through visual recognition, and inventory management. These advancements transform the way retailers interact with customers and manage their operations, driving growth in the retail technology space.
• Enhanced Security and Surveillance Systems: Visual AI is increasingly being used to enhance security and surveillance systems. Innovations include advanced facial recognition, behavior analysis, and automated threat detection. These improvements boost the effectiveness of security systems in public spaces, transportation hubs, and sensitive facilities, contributing to increased safety and security measures.

These trends reshape the visual AI analysis market by driving advancements in edge computing, deep learning, and healthcare applications. The growing adoption in retail and security expands the market's reach and utility, while improvements in technology continue to enhance the capabilities and applications of visual AI systems.

Recent Developments in the Visual AI Analysis Market

The visual AI analysis market has seen several key developments that are influencing its growth and technological evolution. These developments reflect advancements in AI technologies and their applications across different sectors.

• Development of Real-Time Facial Recognition Systems: Recent advancements include the development of highly accurate real-time facial recognition systems. These systems improve security and access control in various applications, from public safety to secure facility access. Enhanced algorithms and faster processing capabilities drive this development, leading to more effective and reliable facial recognition solutions.
• Integration of AI in Autonomous Vehicles: Visual AI technologies are integrated into autonomous vehicles to enhance navigation and safety. Developments include advanced image analysis for object detection, lane tracking, and collision avoidance. These innovations improve the performance and safety of self-driving cars, contributing to the growth of the autonomous vehicle market.
• Advancements in Medical Imaging Analysis: There have been significant advancements in AI-powered medical imaging analysis. Developments include enhanced algorithms for detecting and diagnosing medical conditions from X-rays, MRIs, and CT scans. These advancements improve diagnostic accuracy and efficiency, leading to better patient outcomes and streamlined medical processes.
• Growth of AI-Powered Retail Solutions: The retail sector is experiencing growth in AI-powered visual solutions, such as automated checkout systems and personalized shopping experiences. Developments in visual recognition and analysis transform retail operations, enhance customer experience, and improve inventory management.
• Enhanced Video Analytics for Public Safety: Visual AI systems are being developed to provide advanced video analytics for public safety. Innovations include automated threat detection, behavior analysis, and enhanced surveillance capabilities. These developments improve security measures in public spaces and transportation systems, contributing to safer environments.

These key developments drive significant changes in the visual AI analysis market. Real-time facial recognition, autonomous vehicle integration, medical imaging advancements, retail solutions, and public safety analytics expand the market's applications and enhance its technological capabilities.

Strategic Growth Opportunities for Visual AI Analysis Market

The visual AI analysis market presents several strategic growth opportunities across key applications. These opportunities are driven by advancements in technology and increasing demand for visual analysis solutions.

• Expansion in Healthcare Diagnostics: There is significant growth potential for visual AI in healthcare diagnostics. Opportunities include developing advanced imaging systems for early disease detection, AI-driven diagnostic tools, and telemedicine applications. These solutions can improve diagnostic accuracy and efficiency, addressing the growing need for advanced healthcare technologies.
• Growth in Autonomous Vehicles and Smart Transportation: The autonomous vehicle market offers substantial growth opportunities for visual AI. Applications include enhancing navigation systems, object detection, and collision avoidance. As autonomous vehicles become more prevalent, the demand for advanced visual AI solutions will continue to grow, driving innovation and development in this sector.
• Adoption in Retail and Customer Experience Solutions: Visual AI has significant potential in the retail sector, offering opportunities for automated checkout systems, personalized shopping experiences, and inventory management. These solutions can transform retail operations, enhance customer engagement, and improve operational efficiency, contributing to growth in the retail technology space.
• Advancements in Security and Surveillance Systems: The security and surveillance sector presents growth opportunities for visual AI. Applications include enhanced facial recognition, behavior analysis, and automated threat detection. These solutions can improve public safety and security measures, driving demand for advanced visual AI technologies.
• Integration with Edge Computing for Real-Time Analysis: Integrating visual AI with edge computing technologies offers growth opportunities by enabling real-time data processing at the edge of the network. This integration supports applications in various sectors, including autonomous vehicles, smart cities, and remote monitoring, enhancing performance and reducing latency.

These strategic growth opportunities highlight the potential for visual AI analysis to drive innovation and address evolving needs in healthcare, transportation, retail, security, and edge computing. By focusing on these areas, the market can leverage advancements in technology to support growth and development.

Visual AI Analysis Market Driver and Challenges

The visual AI analysis market is influenced by various drivers and challenges that impact its growth and development. Understanding these factors is crucial for navigating the market and achieving success.

The factors responsible for driving the visual AI analysis market include:

• Advancements in AI and Machine Learning: Technological advancements in AI and machine learning are driving growth in visual AI analysis. Improved algorithms and neural networks enhance the accuracy and efficiency of image and video analysis, expanding the capabilities and applications of visual AI systems.
• Increasing Demand for Real-Time Data Processing: The growing need for real-time data processing is a key driver for the visual AI market. Applications in autonomous vehicles, smart cities, and security require rapid and accurate visual analysis, driving demand for advanced visual AI solutions.
• Expanding Applications in Healthcare: The expanding applications of visual AI in healthcare, such as medical imaging and diagnostics, are driving market growth. The need for accurate and efficient diagnostic tools supports the development and adoption of AI-driven visual solutions in the healthcare sector.
• Growth in Smart City and Surveillance Projects: The development of smart cities and the increased focus on public safety and surveillance are driving demand for visual AI technologies. Advanced video analytics and facial recognition systems are enhancing security and efficiency in urban environments.
• Integration with Edge Computing Technologies: The integration of visual AI with edge computing technologies is driving market growth by enabling real-time data processing at the edge. This trend enhances performance and reduces latency, supporting various applications across different sectors.

Challenges in the visual AI analysis market include:

• Privacy and Data Security Concerns: Privacy and data security are significant challenges in the visual AI market. Handling sensitive information and ensuring compliance with regulations are critical for maintaining trust and addressing security concerns.
• High Costs and Resource Requirements: The development and implementation of advanced visual AI systems can be costly and resource-intensive. High costs associated with technology and infrastructure can be barriers to widespread adoption, particularly for smaller organizations.
• Ethical and Regulatory Issues: Ethical and regulatory issues, such as bias in AI algorithms and the use of surveillance technologies, pose challenges for the market. Addressing these issues is essential for ensuring the responsible use of visual AI and maintaining regulatory compliance.

Advancements in AI technology, increasing demand for real-time processing, and growth in healthcare and smart city applications are key drivers of the visual AI analysis market. However, challenges related to privacy, costs, and ethical considerations need to be addressed to support continued growth and adoption. Balancing these drivers and challenges is crucial for the market's development and success.

List of Visual AI Analysis Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies visual AI analysis companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the visual AI analysis companies profiled in this report include-

• Cambricon
• Clarifai
• CloudSight
• DataRobot
• DeepVisionAI
• EdgeQ
• EyeEM

Visual AI Analysis by Segment

The study includes a forecast for the global visual AI analysis market by type, application, and region.

Visual AI Analysis Market by Type [Analysis by Value from 2019 to 2031]:

• Hardware
• Software

Visual AI Analysis Market by Application [Analysis by Value from 2019 to 2031]:

• Smart Driving
• Financial Services
• Medical Treatment
• Smart City
• Others

Visual AI Analysis Market by Region [Analysis by Value from 2019 to 2031]:

• North America
• Europe
• Asia Pacific
• The Rest of the World

Country Wise Outlook for the Visual AI Analysis Market

The visual AI analysis market is witnessing rapid progress with the development of technology and a rise in demand for sophisticated image and video analysis. The requirement for visual AI, which depends on artificial intelligence for the interpretation of visual data, is indeed growing in every sector. Innovations in algorithms related to machine learning, improvements in hardware efficiencies, and enhanced adoption across a wide range of sectors contribute to this growth. Here is an overview of recent developments in key markets:

• United States: The visual AI analysis market in the United States is growing rapidly. Significant investments have been made in deep learning and computer vision technology. Key developments include improved facial recognition systems, advanced medical imaging diagnostics, and smart surveillance solutions. Technology and startup companies are driving innovation by focusing on achieving increased accuracy and processing speed in visual data analysis, which is an exciting challenge in security, healthcare, and autonomous vehicles, among others.
• China: China is rapidly advancing in visual AI analysis, primarily focusing on surveillance and smart city applications. Companies in China are utilizing advanced AI systems for facial recognition and video analytics integrated within urban infrastructure to improve security and enhance traffic management. Support from the government through research investments is driving rapid development, allowing China to stay ahead in utilizing visual technologies in AI-driven scenarios.
• Germany: Germany applies visual AI analysis in industries and applications related to automotive technology. Newly developed areas include the installation of AI-driven visual inspection systems in manufacturing processes and the creation of autonomous driving technologies. With an emphasis on precision and reliability, companies in Germany enhance quality control and operational efficiency in various industries, contributing to advancements in vehicle safety and automation.
• India: Visual AI analysis is gaining importance in India, with an increased focus on cost-effective and scalable solutions for a wide range of applications. Agriculture monitoring, healthcare diagnostics, and security are some of the new developments in which Indian startups and tech firms are working hard to create more cost-effective AI solutions. These solutions aim to improve crop yields in low-yield situations and diagnose diseases more accurately, especially in rural areas.
• Japan: Japan is making progress in visual AI analysis in the fields of robotics and consumer electronics. Recent innovations involve enhancing AI systems for automation in robotic vision and advanced image analysis for consumer devices. Companies are integrating these technologies into their products and services to provide a seamless user experience and operational efficiency across different sectors, such as manufacturing and personal electronics.

Features of the Global Visual AI Analysis Market

Market Size Estimates: Visual AI analysis market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.

Segmentation Analysis: Visual AI analysis market size by type, application, and region in terms of value ($B).

Regional Analysis: Visual AI analysis market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the visual AI analysis market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the visual AI analysis market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

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This report answers following 11 key questions:

• Q.1. What are some of the most promising, high-growth opportunities for the visual AI analysis market by type (hardware and software), application (smart driving, financial services, medical treatment, smart city, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
• Q.2. Which segments will grow at a faster pace and why?
• Q.3. Which region will grow at a faster pace and why?
• Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
• Q.5. What are the business risks and competitive threats in this market?
• Q.6. What are the emerging trends in this market and the reasons behind them?
• Q.7. What are some of the changing demands of customers in the market?
• Q.8. What are the new developments in the market? Which companies are leading these developments?
• Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
• Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
• Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Global Visual AI Analysis Market : Market Dynamics

• 2.1: Introduction, Background, and Classifications
• 2.2: Supply Chain
• 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2019 to 2031

• 3.1. Macroeconomic Trends (2019-2024) and Forecast (2025-2031)
• 3.2. Global Visual AI Analysis Market Trends (2019-2024) and Forecast (2025-2031)
• 3.3: Global Visual AI Analysis Market by Type
  • 3.3.1: Hardware
  • 3.3.2: Software
• 3.4: Global Visual AI Analysis Market by Application
  • 3.4.1: Smart Driving
  • 3.4.2: Financial Services
  • 3.4.3: Medical Treatment
  • 3.4.4: Smart City
  • 3.4.5: Others

4. Market Trends and Forecast Analysis by Region from 2019 to 2031

• 4.1: Global Visual AI Analysis Market by Region
• 4.2: North American Visual AI Analysis Market
  • 4.2.1: North American Market by Type: Hardware and Software
  • 4.2.2: North American Market by Application: Smart Driving, Financial Services, Medical Treatment, Smart City, and Others
• 4.3: European Visual AI Analysis Market
  • 4.3.1: European Market by Type: Hardware and Software
  • 4.3.2: European Market by Application: Smart Driving, Financial Services, Medical Treatment, Smart City, and Others
• 4.4: APAC Visual AI Analysis Market
  • 4.4.1: APAC Market by Type: Hardware and Software
  • 4.4.2: APAC Market by Application: Smart Driving, Financial Services, Medical Treatment, Smart City, and Others
• 4.5: ROW Visual AI Analysis Market
  • 4.5.1: ROW Market by Type: Hardware and Software
  • 4.5.2: ROW Market by Application: Smart Driving, Financial Services, Medical Treatment, Smart City, and Others

5. Competitor Analysis

• 5.1: Product Portfolio Analysis
• 5.2: Operational Integration
• 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

• 6.1: Growth Opportunity Analysis
  • 6.1.1: Growth Opportunities for the Global Visual AI Analysis Market by Type
  • 6.1.2: Growth Opportunities for the Global Visual AI Analysis Market by Application
  • 6.1.3: Growth Opportunities for the Global Visual AI Analysis Market by Region
• 6.2: Emerging Trends in the Global Visual AI Analysis Market
• 6.3: Strategic Analysis
  • 6.3.1: New Product Development
  • 6.3.2: Capacity Expansion of the Global Visual AI Analysis Market
  • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global Visual AI Analysis Market
  • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

• 7.1: Cambricon
• 7.2: Clarifai
• 7.3: CloudSight
• 7.4: DataRobot
• 7.5: DeepVisionAI
• 7.6: EdgeQ
• 7.7: EyeEM