세계의 합성곱 신경망 시장 : 시장 규모, 점유율, 동향 분석 보고서 - 전개 방식별, 구성요소별, 용도별, 산업별, 지역별 전망 및 예측(2024-2031년)

The Global Convolutional Neural Networks Market size is expected to reach $131.7 billion by 2031, rising at a market growth of 40.2% CAGR during the forecast period.

The North America region witnessed 36% revenue share in this market in 2023. This dominance can be attributed to leading technology companies, significant investments in research and development, and a strong emphasis on adopting advanced AI technologies across various sectors. North America, particularly the United States, has been at the forefront of machine learning and artificial intelligence innovations, resulting in a high demand for CNN applications in the healthcare, automotive, finance, and entertainment industries.

The major strategies followed by the market participants are Product Launches as the key developmental strategy to keep pace with the changing demands of end users. For instance, In September, 2024, NVIDIA Corporation Deep Learning Institute and Dartmouth College unveiled the Generative AI Teaching Kit, developed by, equips educators with advanced tools and practical resources to teach generative AI and large language models. This initiative prepares students to drive innovation in AI-related fields, addressing challenges in healthcare, science, and sustainable technologies. Moreover, In September, 2024, Intel Corporation unveiled Xeon 6 with Performance-cores (P-cores) and Gaudi 3 AI accelerators, addressing the rising demand for cost-effective AI infrastructure. Justin Hotard emphasized the need for choice in hardware and software, enabling customers to enhance performance, efficiency, and security in their data center workloads.

KBV Cardinal Matrix - Convolutional Neural Networks Market Competition Analysis

Based on the Analysis presented in the KBV Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the Convolutional Neural Networks Market. In February, 2024, Microsoft Corporation unveiled Clifford-Steerable Convolutional Neural Networks (CS-CNNs), a new class of $\mathrm{E}(p, q)$-equivariant CNNs that process multivector fields on pseudo-Euclidean spaces $\mathbb{R}^{p,q}$. CS-CNNs leverage Clifford group-equivariant networks to achieve superior performance in fluid dynamics and relativistic electrodynamics forecasting compared to baseline methods. Companies such as Amazon Web Services, Inc., NVIDIA Corporation, and Samsung Electronics Co., Ltd. are some of the key innovators in Convolutional Neural Networks Market.

Market Growth Factors

The explosion of digital content-from social media platforms to e-commerce websites-has created an overwhelming volume of images and videos that require efficient processing and analysis. Organizations seek advanced recognition solutions to categorize, tag, and retrieve this content effectively. CNNs excel in visual recognition tasks, making them essential tools for managing and interpreting large datasets. Thus, increasing demand for advanced image and video recognition solutions propels the market's growth.

Additionally, Wearable devices are increasingly utilized for health monitoring, providing users with real-time data on vital signs, physical activity, and sleep patterns. CNNs facilitate the analysis of complex health data by processing images from sensors, such as those used in heart rate monitoring or blood oxygen level detection. This capability enables wearables to deliver accurate health insights, driving their adoption among health-conscious consumers. Therefore, growing popularity of wearable technology requiring efficient data analysis is driving the growth of the market.

Market Restraining Factors

However, Developing robust and effective CNN models requires extensive research and experimentation. Organizations must invest heavily in R&D to create algorithms that perform well in specific applications. This process often involves hiring specialized personnel, such as data scientists and machine learning engineers, whose salaries can be substantial. The need for ongoing innovation to stay competitive further increases these costs. In conclusion, high development and maintenance costs hamper the market's growth.

The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The above illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Product Launches and Product Expansions.

Deployment Mode Outlook

Based on deployment mode, this market is divided into on-premises and cloud. The cloud segment attained 43% revenue share in the convolutional neural networks market in 2023. This growth is primarily driven by the increasing adoption of cloud-based services, which offer scalable resources, flexibility, and cost-effectiveness for deploying CNN applications. Organizations are increasingly leveraging cloud infrastructure to handle the extensive computational requirements of CNNs, allowing them to process large datasets efficiently without significant upfront investments in hardware.

Component Outlook

Based on components, this market is divided into hardware, software, and services. In 2023, the software segment garnered 34% revenue share in the convolutional neural networks market. This dominance is driven by the increasing demand for advanced software solutions that facilitate the efficient deployment and operation of CNN models across various applications. These software solutions include frameworks, development tools, and platforms that enable CNNs to integrate seamlessly and scalable.

Application Outlook

On the basis of application, this market is segmented into image and video recognition, natural language processing (NLP), medical image analysis, autonomous vehicles, robotics and manufacturing, and others. The natural language processing (NLP) segment recorded 19% revenue share in the convolutional neural networks market in 2023. This can be attributed to the increasing adoption of NLP technologies in various industries, including customer service, healthcare, and finance, where understanding and processing human language is crucial.

Vertical Outlook

By vertical, this market is divided into healthcare, automotive, retail & e-commerce, IT & telecommunications, manufacturing, aerospace & defense, energy & utilities, and others. The automotive segment procured 18% revenue share in the convolutional neural networks market in 2023. This growth is driven by the widespread adoption of CNNs in autonomous driving systems, advanced driver-assistance systems (ADAS), and predictive maintenance. CNNs enable vehicles to recognize objects, pedestrians, and road signs, enhancing safety and driving efficiency.

Regional Outlook

Region-wise, this market is analyzed across North America, Europe, Asia Pacific, and LAMEA. The Asia Pacific region generated 26% revenue share in the convolutional neural networks market in 2023. This growth is fuelled by the rapid adoption of AI technologies in countries like China, Japan, and India, driven by increasing investments in digital transformation and technology infrastructure. The region is witnessing significant advancements in healthcare, e-commerce, and manufacturing sectors, where CNNs are utilized for applications like image and video analysis, predictive maintenance, and natural language processing.

Market Competition and Attributes

The competition in the Convolutional Neural Networks (CNN) market is driven by smaller firms, startups, and academic institutions focused on niche applications and innovations. These players compete through specialized solutions, cost-efficiency, and adaptability in sectors like healthcare, automotive, and robotics, fostering creativity and diversified growth.

Recent Strategies Deployed in the Market

• Aug-2024: IBM Corporation the Telum Processor, featuring on-chip AI inference acceleration for real-time fraud detection in enterprise workloads. Developed over three years, this technology aims to enhance business insights in banking, finance, insurance, and trading applications, with a Telum-based system expected in early 2022.
• Jul-2024: H2O.ai, Inc. unveiled H2O-Danube3, a series of small language models H2O-Danube3-4B (trained on 6T tokens) and H2O-Danube3-500M (trained on 4T tokens). These models, optimized for performance on mobile devices, demonstrate strong metrics across various benchmarks and are available for public use under the Apache 2.0 license.
• Jun-2024: OpenAI, LLC announced the acquisition of Rockset, a real-time database startup, to enhance its AI infrastructure and boost performance across its products, including ChatGPT. Rockset specializes in real-time indexing, allowing instant data processing for quick queries, vital for AI applications. This acquisition will enable users to convert data into actionable intelligence.
• May-2024: OpenAI, LLC unveiled its flagship model, GPT-4o. This multimodal AI can process text, audio, and images, boasting a response time of 232 milliseconds for audio and 320 milliseconds on average, utilizing fillers to manage latency.
• May-2024: Samsung Electronics Co., Ltd. medical diagnostic division announced the acquisition of Sonio SAS, a cloud-based ultrasound OB-GYN reporting software. Sonio develops AI-powered ultrasound software that enhances care for women and infants. Its solutions streamline fetal examinations, enabling healthcare workers to quickly identify prenatal structures and share annotated findings with patients and professionals via QR code.

List of Key Companies Profiled

• NVIDIA Corporation
• Google LLC
• Microsoft Corporation
• IBM Corporation
• Amazon Web Services, Inc. (Amazon.com, Inc.)
• OpenAI, LLC
• Samsung Electronics Co., Ltd. (Samsung Group)
• Intel Corporation
• H2O.ai, Inc.
• Qualcomm Incorporated (Qualcomm Technologies, Inc.)

Global Convolutional Neural Networks Market Report Segmentation

By Deployment Mode

• On-Premise
• Cloud

By Component

• Hardware
• Software
• Services

By Application

• Image & Video Recognition
• Natural Language Processing (NLP)
• Medical Image Analysis
• Autonomous Vehicles
• Robotics & Manufacturing
• Other Application

By Vertical

• Healthcare
• Automotive
• Retail & E-commerce
• IT & Telecommunications
• Manufacturing
• Aerospace & Defense
• Energy & Utilities
• Other Vertical

By Geography

• North America
  • US
  • Canada
  • Mexico
  • Rest of North America
• Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Malaysia
  • Rest of Asia Pacific
• LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
• Rest of LAMEA

Table of Contents

Chapter 1. Market Scope & Methodology

• 1.1 Market Definition
• 1.2 Objectives
• 1.3 Market Scope
• 1.4 Segmentation
  • 1.4.1 Global Convolutional Neural Networks Market, by Deployment Mode
  • 1.4.2 Global Convolutional Neural Networks Market, by Component
  • 1.4.3 Global Convolutional Neural Networks Market, by Application
  • 1.4.4 Global Convolutional Neural Networks Market, by Vertical
  • 1.4.5 Global Convolutional Neural Networks Market, by Geography
• 1.5 Methodology for the research

Chapter 2. Market at a Glance

• 2.1 Key Highlights

Chapter 3. Market Overview

• 3.1 Introduction
  • 3.1.1 Overview
    • 3.1.1.1 Market Composition and Scenario
• 3.2 Key Factors Impacting the Market
  • 3.2.1 Market Drivers
  • 3.2.2 Market Restraints
  • 3.2.3 Market Opportunities
  • 3.2.4 Market Challenges

Chapter 4. Competition Analysis - Global

• 4.1 KBV Cardinal Matrix
• 4.2 Recent Industry Wide Strategic Developments
  • 4.2.1 Partnerships, Collaborations and Agreements
  • 4.2.2 Product Launches and Product Expansions
  • 4.2.3 Acquisition and Mergers
• 4.3 Market Share Analysis, 2023
• 4.4 Top Winning Strategies
  • 4.4.1 Key Leading Strategies: Percentage Distribution (2020-2024)
  • 4.4.2 Key Strategic Move: (Product Launches and Product Expansions : 2020, Aug - 2024, Sep) Leading Players
• 4.5 Porter Five Forces Analysis

Chapter 5. Global Convolutional Neural Networks Market by Deployment Mode

• 5.1 Global On-Premise Market by Region
• 5.2 Global Cloud Market by Region

Chapter 6. Global Convolutional Neural Networks Market by Component

• 6.1 Global Hardware Market by Region
• 6.2 Global Software Market by Region
• 6.3 Global Services Market by Region

Chapter 7. Global Convolutional Neural Networks Market by Application

• 7.1 Global Image & Video Recognition Market by Region
• 7.2 Global Natural Language Processing (NLP) Market by Region
• 7.3 Global Medical Image Analysis Market by Region
• 7.4 Global Autonomous Vehicles Market by Region
• 7.5 Global Robotics & Manufacturing Market by Region
• 7.6 Global Other Application Market by Region

Chapter 8. Global Convolutional Neural Networks Market by Vertical

• 8.1 Global Healthcare Market by Region
• 8.2 Global Automotive Market by Region
• 8.3 Global Retail & E-commerce Market by Region
• 8.4 Global IT & Telecommunications Market by Region
• 8.5 Global Manufacturing Market by Region
• 8.6 Global Aerospace & Defense Market by Region
• 8.7 Global Energy & Utilities Market by Region
• 8.8 Global Other Vertical Market by Region

Chapter 9. Global Convolutional Neural Networks Market by Region

• 9.1 North America Convolutional Neural Networks Market
  • 9.1.1 North America Convolutional Neural Networks Market by Deployment Mode
    • 9.1.1.1 North America On-Premise Market by Region
    • 9.1.1.2 North America Cloud Market by Region
  • 9.1.2 North America Convolutional Neural Networks Market by Component
    • 9.1.2.1 North America Hardware Market by Country
    • 9.1.2.2 North America Software Market by Country
    • 9.1.2.3 North America Services Market by Country
  • 9.1.3 North America Convolutional Neural Networks Market by Application
    • 9.1.3.1 North America Image & Video Recognition Market by Country
    • 9.1.3.2 North America Natural Language Processing (NLP) Market by Country
    • 9.1.3.3 North America Medical Image Analysis Market by Country
    • 9.1.3.4 North America Autonomous Vehicles Market by Country
    • 9.1.3.5 North America Robotics & Manufacturing Market by Country
    • 9.1.3.6 North America Other Application Market by Country
  • 9.1.4 North America Convolutional Neural Networks Market by Vertical
    • 9.1.4.1 North America Healthcare Market by Country
    • 9.1.4.2 North America Automotive Market by Country
    • 9.1.4.3 North America Retail & E-commerce Market by Country
    • 9.1.4.4 North America IT & Telecommunications Market by Country
    • 9.1.4.5 North America Manufacturing Market by Country
    • 9.1.4.6 North America Aerospace & Defense Market by Country
    • 9.1.4.7 North America Energy & Utilities Market by Country
    • 9.1.4.8 North America Other Vertical Market by Country
  • 9.1.5 North America Convolutional Neural Networks Market by Country
    • 9.1.5.1 US Convolutional Neural Networks Market
      • 9.1.5.1.1 US Convolutional Neural Networks Market by Deployment Mode
      • 9.1.5.1.2 US Convolutional Neural Networks Market by Component
      • 9.1.5.1.3 US Convolutional Neural Networks Market by Application
      • 9.1.5.1.4 US Convolutional Neural Networks Market by Vertical
    • 9.1.5.2 Canada Convolutional Neural Networks Market
      • 9.1.5.2.1 Canada Convolutional Neural Networks Market by Deployment Mode
      • 9.1.5.2.2 Canada Convolutional Neural Networks Market by Component
      • 9.1.5.2.3 Canada Convolutional Neural Networks Market by Application
      • 9.1.5.2.4 Canada Convolutional Neural Networks Market by Vertical
    • 9.1.5.3 Mexico Convolutional Neural Networks Market
      • 9.1.5.3.1 Mexico Convolutional Neural Networks Market by Deployment Mode
      • 9.1.5.3.2 Mexico Convolutional Neural Networks Market by Component
      • 9.1.5.3.3 Mexico Convolutional Neural Networks Market by Application
      • 9.1.5.3.4 Mexico Convolutional Neural Networks Market by Vertical
    • 9.1.5.4 Rest of North America Convolutional Neural Networks Market
      • 9.1.5.4.1 Rest of North America Convolutional Neural Networks Market by Deployment Mode
      • 9.1.5.4.2 Rest of North America Convolutional Neural Networks Market by Component
      • 9.1.5.4.3 Rest of North America Convolutional Neural Networks Market by Application
      • 9.1.5.4.4 Rest of North America Convolutional Neural Networks Market by Vertical
• 9.2 Europe Convolutional Neural Networks Market
  • 9.2.1 Europe Convolutional Neural Networks Market by Deployment Mode
    • 9.2.1.1 Europe On-Premise Market by Country
    • 9.2.1.2 Europe Cloud Market by Country
  • 9.2.2 Europe Convolutional Neural Networks Market by Component
    • 9.2.2.1 Europe Hardware Market by Country
    • 9.2.2.2 Europe Software Market by Country
    • 9.2.2.3 Europe Services Market by Country
  • 9.2.3 Europe Convolutional Neural Networks Market by Application
    • 9.2.3.1 Europe Image & Video Recognition Market by Country
    • 9.2.3.2 Europe Natural Language Processing (NLP) Market by Country
    • 9.2.3.3 Europe Medical Image Analysis Market by Country
    • 9.2.3.4 Europe Autonomous Vehicles Market by Country
    • 9.2.3.5 Europe Robotics & Manufacturing Market by Country
    • 9.2.3.6 Europe Other Application Market by Country
  • 9.2.4 Europe Convolutional Neural Networks Market by Vertical
    • 9.2.4.1 Europe Healthcare Market by Country
    • 9.2.4.2 Europe Automotive Market by Country
    • 9.2.4.3 Europe Retail & E-commerce Market by Country
    • 9.2.4.4 Europe IT & Telecommunications Market by Country
    • 9.2.4.5 Europe Manufacturing Market by Country
    • 9.2.4.6 Europe Aerospace & Defense Market by Country
    • 9.2.4.7 Europe Energy & Utilities Market by Country
    • 9.2.4.8 Europe Other Vertical Market by Country
  • 9.2.5 Europe Convolutional Neural Networks Market by Country
    • 9.2.5.1 Germany Convolutional Neural Networks Market
      • 9.2.5.1.1 Germany Convolutional Neural Networks Market by Deployment Mode
      • 9.2.5.1.2 Germany Convolutional Neural Networks Market by Component
      • 9.2.5.1.3 Germany Convolutional Neural Networks Market by Application
      • 9.2.5.1.4 Germany Convolutional Neural Networks Market by Vertical
    • 9.2.5.2 UK Convolutional Neural Networks Market
      • 9.2.5.2.1 UK Convolutional Neural Networks Market by Deployment Mode
      • 9.2.5.2.2 UK Convolutional Neural Networks Market by Component
      • 9.2.5.2.3 UK Convolutional Neural Networks Market by Application
      • 9.2.5.2.4 UK Convolutional Neural Networks Market by Vertical
    • 9.2.5.3 France Convolutional Neural Networks Market
      • 9.2.5.3.1 France Convolutional Neural Networks Market by Deployment Mode
      • 9.2.5.3.2 France Convolutional Neural Networks Market by Component
      • 9.2.5.3.3 France Convolutional Neural Networks Market by Application
      • 9.2.5.3.4 France Convolutional Neural Networks Market by Vertical
    • 9.2.5.4 Russia Convolutional Neural Networks Market
      • 9.2.5.4.1 Russia Convolutional Neural Networks Market by Deployment Mode
      • 9.2.5.4.2 Russia Convolutional Neural Networks Market by Component
      • 9.2.5.4.3 Russia Convolutional Neural Networks Market by Application
      • 9.2.5.4.4 Russia Convolutional Neural Networks Market by Vertical
    • 9.2.5.5 Spain Convolutional Neural Networks Market
      • 9.2.5.5.1 Spain Convolutional Neural Networks Market by Deployment Mode
      • 9.2.5.5.2 Spain Convolutional Neural Networks Market by Component
      • 9.2.5.5.3 Spain Convolutional Neural Networks Market by Application
      • 9.2.5.5.4 Spain Convolutional Neural Networks Market by Vertical
    • 9.2.5.6 Italy Convolutional Neural Networks Market
      • 9.2.5.6.1 Italy Convolutional Neural Networks Market by Deployment Mode
      • 9.2.5.6.2 Italy Convolutional Neural Networks Market by Component
      • 9.2.5.6.3 Italy Convolutional Neural Networks Market by Application
      • 9.2.5.6.4 Italy Convolutional Neural Networks Market by Vertical
    • 9.2.5.7 Rest of Europe Convolutional Neural Networks Market
      • 9.2.5.7.1 Rest of Europe Convolutional Neural Networks Market by Deployment Mode
      • 9.2.5.7.2 Rest of Europe Convolutional Neural Networks Market by Component
      • 9.2.5.7.3 Rest of Europe Convolutional Neural Networks Market by Application
      • 9.2.5.7.4 Rest of Europe Convolutional Neural Networks Market by Vertical
• 9.3 Asia Pacific Convolutional Neural Networks Market
  • 9.3.1 Asia Pacific Convolutional Neural Networks Market by Deployment Mode
    • 9.3.1.1 Asia Pacific On-Premise Market by Country
    • 9.3.1.2 Asia Pacific Cloud Market by Country
  • 9.3.2 Asia Pacific Convolutional Neural Networks Market by Component
    • 9.3.2.1 Asia Pacific Hardware Market by Country
    • 9.3.2.2 Asia Pacific Software Market by Country
    • 9.3.2.3 Asia Pacific Services Market by Country
  • 9.3.3 Asia Pacific Convolutional Neural Networks Market by Application
    • 9.3.3.1 Asia Pacific Image & Video Recognition Market by Country
    • 9.3.3.2 Asia Pacific Natural Language Processing (NLP) Market by Country
    • 9.3.3.3 Asia Pacific Medical Image Analysis Market by Country
    • 9.3.3.4 Asia Pacific Autonomous Vehicles Market by Country
    • 9.3.3.5 Asia Pacific Robotics & Manufacturing Market by Country
    • 9.3.3.6 Asia Pacific Other Application Market by Country
  • 9.3.4 Asia Pacific Convolutional Neural Networks Market by Vertical
    • 9.3.4.1 Asia Pacific Healthcare Market by Country
    • 9.3.4.2 Asia Pacific Automotive Market by Country
    • 9.3.4.3 Asia Pacific Retail & E-commerce Market by Country
    • 9.3.4.4 Asia Pacific IT & Telecommunications Market by Country
    • 9.3.4.5 Asia Pacific Manufacturing Market by Country
    • 9.3.4.6 Asia Pacific Aerospace & Defense Market by Country
    • 9.3.4.7 Asia Pacific Energy & Utilities Market by Country
    • 9.3.4.8 Asia Pacific Other Vertical Market by Country
  • 9.3.5 Asia Pacific Convolutional Neural Networks Market by Country
    • 9.3.5.1 China Convolutional Neural Networks Market
      • 9.3.5.1.1 China Convolutional Neural Networks Market by Deployment Mode
      • 9.3.5.1.2 China Convolutional Neural Networks Market by Component
      • 9.3.5.1.3 China Convolutional Neural Networks Market by Application
      • 9.3.5.1.4 China Convolutional Neural Networks Market by Vertical
    • 9.3.5.2 Japan Convolutional Neural Networks Market
      • 9.3.5.2.1 Japan Convolutional Neural Networks Market by Deployment Mode
      • 9.3.5.2.2 Japan Convolutional Neural Networks Market by Component
      • 9.3.5.2.3 Japan Convolutional Neural Networks Market by Application
      • 9.3.5.2.4 Japan Convolutional Neural Networks Market by Vertical
    • 9.3.5.3 India Convolutional Neural Networks Market
      • 9.3.5.3.1 India Convolutional Neural Networks Market by Deployment Mode
      • 9.3.5.3.2 India Convolutional Neural Networks Market by Component
      • 9.3.5.3.3 India Convolutional Neural Networks Market by Application
      • 9.3.5.3.4 India Convolutional Neural Networks Market by Vertical
    • 9.3.5.4 South Korea Convolutional Neural Networks Market
      • 9.3.5.4.1 South Korea Convolutional Neural Networks Market by Deployment Mode
      • 9.3.5.4.2 South Korea Convolutional Neural Networks Market by Component
      • 9.3.5.4.3 South Korea Convolutional Neural Networks Market by Application
      • 9.3.5.4.4 South Korea Convolutional Neural Networks Market by Vertical
    • 9.3.5.5 Australia Convolutional Neural Networks Market
      • 9.3.5.5.1 Australia Convolutional Neural Networks Market by Deployment Mode
      • 9.3.5.5.2 Australia Convolutional Neural Networks Market by Component
      • 9.3.5.5.3 Australia Convolutional Neural Networks Market by Application
      • 9.3.5.5.4 Australia Convolutional Neural Networks Market by Vertical
    • 9.3.5.6 Malaysia Convolutional Neural Networks Market
      • 9.3.5.6.1 Malaysia Convolutional Neural Networks Market by Deployment Mode
      • 9.3.5.6.2 Malaysia Convolutional Neural Networks Market by Component
      • 9.3.5.6.3 Malaysia Convolutional Neural Networks Market by Application
      • 9.3.5.6.4 Malaysia Convolutional Neural Networks Market by Vertical
    • 9.3.5.7 Rest of Asia Pacific Convolutional Neural Networks Market
      • 9.3.5.7.1 Rest of Asia Pacific Convolutional Neural Networks Market by Deployment Mode
      • 9.3.5.7.2 Rest of Asia Pacific Convolutional Neural Networks Market by Component
      • 9.3.5.7.3 Rest of Asia Pacific Convolutional Neural Networks Market by Application
      • 9.3.5.7.4 Rest of Asia Pacific Convolutional Neural Networks Market by Vertical
• 9.4 LAMEA Convolutional Neural Networks Market
  • 9.4.1 LAMEA Convolutional Neural Networks Market by Deployment Mode
    • 9.4.1.1 LAMEA On-Premise Market by Country
    • 9.4.1.2 LAMEA Cloud Market by Country
  • 9.4.2 LAMEA Convolutional Neural Networks Market by Component
    • 9.4.2.1 LAMEA Hardware Market by Country
    • 9.4.2.2 LAMEA Software Market by Country
    • 9.4.2.3 LAMEA Services Market by Country
  • 9.4.3 LAMEA Convolutional Neural Networks Market by Application
    • 9.4.3.1 LAMEA Image & Video Recognition Market by Country
    • 9.4.3.2 LAMEA Natural Language Processing (NLP) Market by Country
    • 9.4.3.3 LAMEA Medical Image Analysis Market by Country
    • 9.4.3.4 LAMEA Autonomous Vehicles Market by Country
    • 9.4.3.5 LAMEA Robotics & Manufacturing Market by Country
    • 9.4.3.6 LAMEA Other Application Market by Country
  • 9.4.4 LAMEA Convolutional Neural Networks Market by Vertical
    • 9.4.4.1 LAMEA Healthcare Market by Country
    • 9.4.4.2 LAMEA Automotive Market by Country
    • 9.4.4.3 LAMEA Retail & E-commerce Market by Country
    • 9.4.4.4 LAMEA IT & Telecommunications Market by Country
    • 9.4.4.5 LAMEA Manufacturing Market by Country
    • 9.4.4.6 LAMEA Aerospace & Defense Market by Country
    • 9.4.4.7 LAMEA Energy & Utilities Market by Country
    • 9.4.4.8 LAMEA Other Vertical Market by Country
  • 9.4.5 LAMEA Convolutional Neural Networks Market by Country
    • 9.4.5.1 Brazil Convolutional Neural Networks Market
      • 9.4.5.1.1 Brazil Convolutional Neural Networks Market by Deployment Mode
      • 9.4.5.1.2 Brazil Convolutional Neural Networks Market by Component
      • 9.4.5.1.3 Brazil Convolutional Neural Networks Market by Application
      • 9.4.5.1.4 Brazil Convolutional Neural Networks Market by Vertical
    • 9.4.5.2 Argentina Convolutional Neural Networks Market
      • 9.4.5.2.1 Argentina Convolutional Neural Networks Market by Deployment Mode
      • 9.4.5.2.2 Argentina Convolutional Neural Networks Market by Component
      • 9.4.5.2.3 Argentina Convolutional Neural Networks Market by Application
      • 9.4.5.2.4 Argentina Convolutional Neural Networks Market by Vertical
    • 9.4.5.3 UAE Convolutional Neural Networks Market
      • 9.4.5.3.1 UAE Convolutional Neural Networks Market by Deployment Mode
      • 9.4.5.3.2 UAE Convolutional Neural Networks Market by Component
      • 9.4.5.3.3 UAE Convolutional Neural Networks Market by Application
      • 9.4.5.3.4 UAE Convolutional Neural Networks Market by Vertical
    • 9.4.5.4 Saudi Arabia Convolutional Neural Networks Market
      • 9.4.5.4.1 Saudi Arabia Convolutional Neural Networks Market by Deployment Mode
      • 9.4.5.4.2 Saudi Arabia Convolutional Neural Networks Market by Component
      • 9.4.5.4.3 Saudi Arabia Convolutional Neural Networks Market by Application
      • 9.4.5.4.4 Saudi Arabia Convolutional Neural Networks Market by Vertical
    • 9.4.5.5 South Africa Convolutional Neural Networks Market
      • 9.4.5.5.1 South Africa Convolutional Neural Networks Market by Deployment Mode
      • 9.4.5.5.2 South Africa Convolutional Neural Networks Market by Component
      • 9.4.5.5.3 South Africa Convolutional Neural Networks Market by Application
      • 9.4.5.5.4 South Africa Convolutional Neural Networks Market by Vertical
    • 9.4.5.6 Nigeria Convolutional Neural Networks Market
      • 9.4.5.6.1 Nigeria Convolutional Neural Networks Market by Deployment Mode
      • 9.4.5.6.2 Nigeria Convolutional Neural Networks Market by Component
      • 9.4.5.6.3 Nigeria Convolutional Neural Networks Market by Application
      • 9.4.5.6.4 Nigeria Convolutional Neural Networks Market by Vertical
    • 9.4.5.7 Rest of LAMEA Convolutional Neural Networks Market
      • 9.4.5.7.1 Rest of LAMEA Convolutional Neural Networks Market by Deployment Mode
      • 9.4.5.7.2 Rest of LAMEA Convolutional Neural Networks Market by Component
      • 9.4.5.7.3 Rest of LAMEA Convolutional Neural Networks Market by Application
      • 9.4.5.7.4 Rest of LAMEA Convolutional Neural Networks Market by Vertical

Chapter 10. Company Profiles

• 10.1 NVIDIA Corporation
  • 10.1.1 Company Overview
  • 10.1.2 Financial Analysis
  • 10.1.3 Segmental and Regional Analysis
  • 10.1.4 Research & Development Expenses
  • 10.1.5 Recent strategies and developments:
    • 10.1.5.1 Product Launches and Product Expansions:
  • 10.1.6 SWOT Analysis
• 10.2 Google LLC
  • 10.2.1 Company Overview
  • 10.2.2 Financial Analysis
  • 10.2.3 Segmental and Regional Analysis
  • 10.2.4 Research & Development Expense
  • 10.2.5 Recent strategies and developments:
    • 10.2.5.1 Product Launches and Product Expansions:
  • 10.2.6 SWOT Analysis
• 10.3 Microsoft Corporation
  • 10.3.1 Company Overview
  • 10.3.2 Financial Analysis
  • 10.3.3 Segmental and Regional Analysis
  • 10.3.4 Research & Development Expenses
  • 10.3.5 Recent strategies and developments:
    • 10.3.5.1 Product Launches and Product Expansions:
  • 10.3.6 SWOT Analysis
• 10.4 IBM Corporation
  • 10.4.1 Company Overview
  • 10.4.2 Financial Analysis
  • 10.4.3 Regional & Segmental Analysis
  • 10.4.4 Research & Development Expenses
  • 10.4.5 Recent strategies and developments:
    • 10.4.5.1 Product Launches and Product Expansions:
  • 10.4.6 SWOT Analysis
• 10.5 Amazon Web Services, Inc. (Amazon.com, Inc.)
  • 10.5.1 Company Overview
  • 10.5.2 Financial Analysis
  • 10.5.3 Segmental Analysis
  • 10.5.4 Recent strategies and developments:
    • 10.5.4.1 Partnerships, Collaborations, and Agreements:
    • 10.5.4.2 Product Launches and Product Expansions:
  • 10.5.5 SWOT Analysis
• 10.6 OpenAI, L.L.C.
  • 10.6.1 Company Overview
  • 10.6.2 Recent strategies and developments:
    • 10.6.2.1 Product Launches and Product Expansions:
    • 10.6.2.2 Acquisition and Mergers:
  • 10.6.3 SWOT Analysis
• 10.7 Samsung Electronics Co., Ltd. (Samsung Group)
  • 10.7.1 Company Overview
  • 10.7.2 Financial Analysis
  • 10.7.3 Segmental and Regional Analysis
  • 10.7.4 Research & Development Expenses
  • 10.7.5 Recent strategies and developments:
    • 10.7.5.1 Product Launches and Product Expansions:
    • 10.7.5.2 Acquisition and Mergers:
  • 10.7.6 SWOT Analysis
• 10.8 Intel Corporation
  • 10.8.1 Company Overview
  • 10.8.2 Financial Analysis
  • 10.8.3 Segmental and Regional Analysis
  • 10.8.4 Research & Development Expenses
  • 10.8.5 Recent strategies and developments:
    • 10.8.5.1 Product Launches and Product Expansions:
  • 10.8.6 SWOT Analysis
• 10.9 H2O.ai, Inc.
  • 10.9.1 Company Overview
  • 10.9.2 Recent strategies and developments:
    • 10.9.2.1 Partnerships, Collaborations, and Agreements:
    • 10.9.2.2 Product Launches and Product Expansions:
• 10.10. Qualcomm Incorporated (Qualcomm Technologies, Inc.)
  • 10.10.1 Company Overview
  • 10.10.2 Financial Analysis
  • 10.10.3 Segmental and Regional Analysis
  • 10.10.4 Research & Development Expense
  • 10.10.5 Recent strategies and developments:
    • 10.10.5.1 Product Launches and Product Expansions:
  • 10.10.6 SWOT Analysis

Chapter 11. Winning Imperatives for Convolutional Neural Networks Market