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封面
市场调查报告书
商品编码
1922520

日本深度学习市场按产品类型、应用、最终用户产业、架构和地区划分，2026-2034 年

Japan Deep Learning Market Report by Product Type, Application, End Use Industry, Architecture, and Region 2026-2034
出版日期: | 出版商: IMARC | 英文 119 Pages | 商品交期: 5-7个工作天内

价格
简介目录

2025年，日本深度学习市场规模达24.945亿美元。展望未来，IMARC集团预测，到2034年，该市场规模将达到363.549亿美元，2026年至2034年的复合年增长率（CAGR）为34.68%。来自社交媒体、物联网设备和感测器等各种来源的数位资料快速成长，为深度学习演算法提供了丰富的资讯来源，从而推动了市场成长。

深度学习是人工智慧的一个分支，它模仿人脑的神经网路来解决复杂问题。它涉及训练由多层相互连接的人工神经元组成的深度神经网络，使其能够从数据中学习模式和表征。这些网路擅长影像识别、语音辨识、自然语言处理，甚至自主决策等任务。深度学习的优点在于能够自动发现和提取原始资料中的特征，从而无需人工进行特征工程。有效的模型训练需要大规模资料集和高效能运算硬件，尤其是GPU。典型的深度学习架构包括用于影像分析的卷积类神经网路（CNN）和用于时间序列资料的循环神经网路（RNN）。深度学习的应用范围非常广泛，包括自动驾驶汽车、医疗诊断和建议系统。其持续发展和创新使机器能够像人类一样学习和决策，使其成为一项具有变革潜力的技术，并有望彻底改变各个产业。

日本深度学习市场趋势：

日本深度学习市场的发展受到多种因素的共同驱动，这些因素共同改变了人工智慧（AI）的模式。首先，数据可用性的指数级增长，以及巨量资料分析的兴起，为深度学习演算法的开发奠定了基础。此外，GPU技术和云端运算的创新不断提升运算能力，使得以前所未有的规模和速度训练深度神经网路成为可能。同时，医疗保健、金融和自动驾驶汽车等行业对深度学习的日益普及，也推动了对深度学习解决方案的需求激增。这种快速成长的需求不仅源自于其在提升决策和自动化方面的潜力，也源自于从海量资料集中提取有意义洞见的迫切需求。总而言之，丰富的数据、先进的运算能力、不断扩展的应用领域以及便捷的工具，预计将共同推动日本深度学习市场的发展，并为该领域的持续成长和创新奠定基础。

本报告解答的关键问题

  • 日本深度学习市场目前发展状况如何？未来几年又将如何发展？
  • 新冠疫情对日本深度学习市场产生了哪些影响？
  • 日本深度学习市场依产品类型分類的组成是怎样的？
  • 日本深度学习市场按应用领域分類的组成是怎样的？
  • 日本深度学习市场依终端用户产业分類的组成是怎样的？
  • 日本深度学习市场依架构分類的组成是怎样的？
  • 日本深度学习市场价值链包含哪些阶段？
  • 日本深度学习市场的主要驱动因素和挑战是什么？
  • 日本深度学习市场的结构是怎么样的？主要企业有哪些？
  • 日本深度学习市场竞争有多激烈？

目录

第一章：序言

第二章：调查范围与调查方法

  • 调查目标
  • 相关利益者
  • 数据来源
  • 市场估值
  • 调查方法

第三章执行摘要

第四章：日本深度学习市场：简介

  • 概述
  • 市场动态
  • 产业趋势
  • 竞争资讯

第五章 日本深度学习市场概览

  • 过去和当前的市场趋势（2020-2025）
  • 市场预测（2026-2034）

第六章：日本深度学习市场：依产品类型划分

  • 软体
  • 服务
  • 硬体

第七章 日本深度学习市场：依应用领域划分

  • 影像识别
  • 讯号识别
  • 资料探勘
  • 其他的

第八章：日本深度学习市场：依最终用户产业划分

  • 安全
  • 製造业
  • 零售
  • 车
  • 卫生保健
  • 农业
  • 其他的

第九章：日本深度学习市场：依架构划分

  • RNN
  • CNN
  • DBN
  • DSN
  • GRU

第十章：日本深度学习市场：依地区划分

  • 关东地区
  • 关西、近畿地区
  • 中部地区
  • 九州和冲绳地区
  • 东北部地区
  • 中国地区
  • 北海道地区
  • 四国地区

第十一章：日本深度学习市场：竞争格局

  • 概述
  • 市场结构
  • 市场公司定位
  • 关键成功策略
  • 竞争对手仪錶板
  • 企业估值象限

第十二章主要企业概况

第十三章：日本深度学习市场：产业分析

  • 驱动因素、限制因素和机会
  • 波特五力分析
  • 价值链分析

第十四章附录

简介目录
Product Code: SR112026A19285

Japan deep learning market size reached USD 2,494.5 Million in 2025 . Looking forward, IMARC Group expects the market to reach USD 36,354.9 Million by 2034 , exhibiting a growth rate (CAGR) of 34.68% during 2026-2034 . The increasing proliferation of digital data from various sources, including social media, IoT devices, and sensors, that provides a rich source of information for deep learning algorithms, is driving the market.

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Deep learning is a subset of artificial intelligence that mimics the human brain's neural networks to solve complex tasks. It involves training deep neural networks, which are composed of many interconnected layers of artificial neurons, to learn patterns and representations from data. These networks excel at tasks like image and speech recognition, natural language processing, and even autonomous decision-making. Deep learning's power lies in its ability to automatically discover and extract features from raw data, eliminating the need for manual feature engineering. It relies on large datasets and powerful computing hardware, particularly GPUs, to train models effectively. Popular deep learning architectures include convolutional neural networks (CNNs) for image analysis and recurrent neural networks (RNNs) for sequential data. The applications of deep learning are vast and include self-driving cars, medical diagnosis, recommendation systems, and more. Its continuous development and innovation have made it a transformative technology with the potential to revolutionize various industries by enabling machines to learn and make decisions like humans.

JAPAN DEEP LEARNING MARKET TRENDS:

The deep learning market in Japan is propelled by a confluence of factors that have transformed the landscape of artificial intelligence (AI). Firstly, the exponential growth of data availability, coupled with the rise of big data analytics, has paved the way for deep learning algorithms to thrive. Moreover, the continuous advancement in computing power, driven by innovations in GPU technology and cloud computing, has made it feasible to train deep neural networks at an unprecedented scale and speed. Furthermore, the increased adoption of deep learning across industries such as healthcare, finance, and autonomous vehicles has led to a surge in demand for deep learning solutions. This burgeoning demand is not only fueled by the promise of improved decision-making and automation but also by the escalating need to extract meaningful insights from vast datasets. In sum, the deep learning market in Japan is expected to be driven by a synergy of data abundance, computational prowess, expanding application domains, and accessible tools, setting the stage for continued growth and innovation in the field.

JAPAN DEEP LEARNING MARKET SEGMENTATION:

Product Type Insights:

  • To get detailed segment analysis of this market Request Sample
  • Software
  • Services
  • Hardware
  • Software
  • Services
  • Hardware

Application Insights:

  • Image Recognition
  • Signal Recognition
  • Data Mining
  • Others
  • Image Recognition
  • Signal Recognition
  • Data Mining
  • Others

End Use Industry Insights:

  • Security
  • Manufacturing
  • Retail
  • Automotive
  • Healthcare
  • Agriculture
  • Others
  • Security
  • Manufacturing
  • Retail
  • Automotive
  • Healthcare
  • Agriculture
  • Others

Architecture Insights:

  • RNN
  • CNN
  • DBN
  • DSN
  • GRU
  • RNN
  • CNN
  • DBN
  • DSN
  • GRU

Regional Insights:

  • To get detailed regional analysis of this market Request Sample
  • Kanto Region
  • Kansai/Kinki Region
  • Central/ Chubu Region
  • Kyushu-Okinawa Region
  • Tohoku Region
  • Chugoku Region
  • Hokkaido Region
  • Shikoku Region
  • Kanto Region
  • Kansai/Kinki Region
  • Central/ Chubu Region
  • Kyushu-Okinawa Region
  • Tohoku Region
  • Chugoku Region
  • Hokkaido Region
  • Shikoku Region
  • The report has also provided a comprehensive analysis of all the major regional markets, which include Kanto Region, Kansai/Kinki Region, Central/Chubu Region, Kyushu-Okinawa Region, Tohoku Region, Chugoku Region, Hokkaido Region, and Shikoku Region.

COMPETITIVE LANDSCAPE:

The market research report has also provided a comprehensive analysis of the competitive landscape. Competitive analysis such as market structure, key player positioning, top winning strategies, competitive dashboard, and company evaluation quadrant has been covered in the report. Also, detailed profiles of all major companies have been provided.

  • KEY QUESTIONS ANSWERED IN THIS REPORT
  • How has the Japan deep learning market performed so far and how will it perform in the coming years?
  • What has been the impact of COVID-19 on the Japan deep learning market?
  • What is the breakup of the Japan deep learning market on the basis of product type?
  • What is the breakup of the Japan deep learning market on the basis of application?
  • What is the breakup of the Japan deep learning market on the basis of end use industry?
  • What is the breakup of the Japan deep learning market on the basis of architecture?
  • What are the various stages in the value chain of the Japan deep learning market?
  • What are the key driving factors and challenges in the Japan deep learning?
  • What is the structure of the Japan deep learning market and who are the key players?
  • What is the degree of competition in the Japan deep learning market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Japan Deep Learning Market - Introduction

  • 4.1 Overview
  • 4.2 Market Dynamics
  • 4.3 Industry Trends
  • 4.4 Competitive Intelligence

5 Japan Deep Learning Market Landscape

  • 5.1 Historical and Current Market Trends (2020-2025)
  • 5.2 Market Forecast (2026-2034)

6 Japan Deep Learning Market - Breakup by Product Type

  • 6.1 Software
    • 6.1.1 Overview
    • 6.1.2 Historical and Current Market Trends (2020-2025)
    • 6.1.3 Market Forecast (2026-2034)
  • 6.2 Services
    • 6.2.1 Overview
    • 6.2.2 Historical and Current Market Trends (2020-2025)
    • 6.2.3 Market Forecast (2026-2034)
  • 6.3 Hardware
    • 6.3.1 Overview
    • 6.3.2 Historical and Current Market Trends (2020-2025)
    • 6.3.3 Market Forecast (2026-2034)

7 Japan Deep Learning Market - Breakup by Application

  • 7.1 Image Recognition
    • 7.1.1 Overview
    • 7.1.2 Historical and Current Market Trends (2020-2025)
    • 7.1.3 Market Forecast (2026-2034)
  • 7.2 Signal Recognition
    • 7.2.1 Overview
    • 7.2.2 Historical and Current Market Trends (2020-2025)
    • 7.2.3 Market Forecast (2026-2034)
  • 7.3 Data Mining
    • 7.3.1 Overview
    • 7.3.2 Historical and Current Market Trends (2020-2025)
    • 7.3.3 Market Forecast (2026-2034)
  • 7.4 Others
    • 7.4.1 Historical and Current Market Trends (2020-2025)
    • 7.4.2 Market Forecast (2026-2034)

8 Japan Deep Learning Market - Breakup by End Use Industry

  • 8.1 Security
    • 8.1.1 Overview
    • 8.1.2 Historical and Current Market Trends (2020-2025)
    • 8.1.3 Market Forecast (2026-2034)
  • 8.2 Manufacturing
    • 8.2.1 Overview
    • 8.2.2 Historical and Current Market Trends (2020-2025)
    • 8.2.3 Market Forecast (2026-2034)
  • 8.3 Retail
    • 8.3.1 Overview
    • 8.3.2 Historical and Current Market Trends (2020-2025)
    • 8.3.3 Market Forecast (2026-2034)
  • 8.4 Automotive
    • 8.4.1 Overview
    • 8.4.2 Historical and Current Market Trends (2020-2025)
    • 8.4.3 Market Forecast (2026-2034)
  • 8.5 Healthcare
    • 8.5.1 Overview
    • 8.5.2 Historical and Current Market Trends (2020-2025)
    • 8.5.3 Market Forecast (2026-2034)
  • 8.6 Agriculture
    • 8.6.1 Overview
    • 8.6.2 Historical and Current Market Trends (2020-2025)
    • 8.6.3 Market Forecast (2026-2034)
  • 8.7 Others
    • 8.7.1 Historical and Current Market Trends (2020-2025)
    • 8.7.2 Market Forecast (2026-2034)

9 Japan Deep Learning Market - Breakup by Architecture

  • 9.1 RNN
    • 9.1.1 Overview
    • 9.1.2 Historical and Current Market Trends (2020-2025)
    • 9.1.3 Market Forecast (2026-2034)
  • 9.2 CNN
    • 9.2.1 Overview
    • 9.2.2 Historical and Current Market Trends (2020-2025)
    • 9.2.3 Market Forecast (2026-2034)
  • 9.3 DBN
    • 9.3.1 Overview
    • 9.3.2 Historical and Current Market Trends (2020-2025)
    • 9.3.3 Market Forecast (2026-2034)
  • 9.4 DSN
    • 9.4.1 Overview
    • 9.4.2 Historical and Current Market Trends (2020-2025)
    • 9.4.3 Market Forecast (2026-2034)
  • 9.5 GRU
    • 9.5.1 Overview
    • 9.5.2 Historical and Current Market Trends (2020-2025)
    • 9.5.3 Market Forecast (2026-2034)

10 Japan Deep Learning Market - Breakup by Region

  • 10.1 Kanto Region
    • 10.1.1 Overview
    • 10.1.2 Historical and Current Market Trends (2020-2025)
    • 10.1.3 Market Breakup by Product Type
    • 10.1.4 Market Breakup by Application
    • 10.1.5 Market Breakup by End Use Industry
    • 10.1.6 Market Breakup by Architecture
    • 10.1.7 Key Players
    • 10.1.8 Market Forecast (2026-2034)
  • 10.2 Kansai/Kinki Region
    • 10.2.1 Overview
    • 10.2.2 Historical and Current Market Trends (2020-2025)
    • 10.2.3 Market Breakup by Product Type
    • 10.2.4 Market Breakup by Application
    • 10.2.5 Market Breakup by End Use Industry
    • 10.2.6 Market Breakup by Architecture
    • 10.2.7 Key Players
    • 10.2.8 Market Forecast (2026-2034)
  • 10.3 Central/ Chubu Region
    • 10.3.1 Overview
    • 10.3.2 Historical and Current Market Trends (2020-2025)
    • 10.3.3 Market Breakup by Product Type
    • 10.3.4 Market Breakup by Application
    • 10.3.5 Market Breakup by End Use Industry
    • 10.3.6 Market Breakup by Architecture
    • 10.3.7 Key Players
    • 10.3.8 Market Forecast (2026-2034)
  • 10.4 Kyushu-Okinawa Region
    • 10.4.1 Overview
    • 10.4.2 Historical and Current Market Trends (2020-2025)
    • 10.4.3 Market Breakup by Product Type
    • 10.4.4 Market Breakup by Application
    • 10.4.5 Market Breakup by End Use Industry
    • 10.4.6 Market Breakup by Architecture
    • 10.4.7 Key Players
    • 10.4.8 Market Forecast (2026-2034)
  • 10.5 Tohoku Region
    • 10.5.1 Overview
    • 10.5.2 Historical and Current Market Trends (2020-2025)
    • 10.5.3 Market Breakup by Product Type
    • 10.5.4 Market Breakup by Application
    • 10.5.5 Market Breakup by End Use Industry
    • 10.5.6 Market Breakup by Architecture
    • 10.5.7 Key Players
    • 10.5.8 Market Forecast (2026-2034)
  • 10.6 Chugoku Region
    • 10.6.1 Overview
    • 10.6.2 Historical and Current Market Trends (2020-2025)
    • 10.6.3 Market Breakup by Product Type
    • 10.6.4 Market Breakup by Application
    • 10.6.5 Market Breakup by End Use Industry
    • 10.6.6 Market Breakup by Architecture
    • 10.6.7 Key Players
    • 10.6.8 Market Forecast (2026-2034)
  • 10.7 Hokkaido Region
    • 10.7.1 Overview
    • 10.7.2 Historical and Current Market Trends (2020-2025)
    • 10.7.3 Market Breakup by Product Type
    • 10.7.4 Market Breakup by Application
    • 10.7.5 Market Breakup by End Use Industry
    • 10.7.6 Market Breakup by Architecture
    • 10.7.7 Key Players
    • 10.7.8 Market Forecast (2026-2034)
  • 10.8 Shikoku Region
    • 10.8.1 Overview
    • 10.8.2 Historical and Current Market Trends (2020-2025)
    • 10.8.3 Market Breakup by Product Type
    • 10.8.4 Market Breakup by Application
    • 10.8.5 Market Breakup by End Use Industry
    • 10.8.6 Market Breakup by Architecture
    • 10.8.7 Key Players
    • 10.8.8 Market Forecast (2026-2034)

11 Japan Deep Learning Market - Competitive Landscape

  • 11.1 Overview
  • 11.2 Market Structure
  • 11.3 Market Player Positioning
  • 11.4 Top Winning Strategies
  • 11.5 Competitive Dashboard
  • 11.6 Company Evaluation Quadrant

12 Profiles of Key Players

  • 12.1 Company A
    • 12.1.1 Business Overview
    • 12.1.2 Services Offered
    • 12.1.3 Business Strategies
    • 12.1.4 SWOT Analysis
    • 12.1.5 Major News and Events
  • 12.2 Company B
    • 12.2.1 Business Overview
    • 12.2.2 Services Offered
    • 12.2.3 Business Strategies
    • 12.2.4 SWOT Analysis
    • 12.2.5 Major News and Events
  • 12.3 Company C
    • 12.3.1 Business Overview
    • 12.3.2 Services Offered
    • 12.3.3 Business Strategies
    • 12.3.4 SWOT Analysis
    • 12.3.5 Major News and Events
  • 12.4 Company D
    • 12.4.1 Business Overview
    • 12.4.2 Services Offered
    • 12.4.3 Business Strategies
    • 12.4.4 SWOT Analysis
    • 12.4.5 Major News and Events
  • 12.5 Company E
    • 12.5.1 Business Overview
    • 12.5.2 Services Offered
    • 12.5.3 Business Strategies
    • 12.5.4 SWOT Analysis
    • 12.5.5 Major News and Events

13 Japan Deep Learning Market - Industry Analysis

  • 13.1 Drivers, Restraints, and Opportunities
    • 13.1.1 Overview
    • 13.1.2 Drivers
    • 13.1.3 Restraints
    • 13.1.4 Opportunities
  • 13.2 Porters Five Forces Analysis
    • 13.2.1 Overview
    • 13.2.2 Bargaining Power of Buyers
    • 13.2.3 Bargaining Power of Suppliers
    • 13.2.4 Degree of Competition
    • 13.2.5 Threat of New Entrants
    • 13.2.6 Threat of Substitutes
  • 13.3 Value Chain Analysis

14 Appendix