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市場調查報告書
商品編碼
1922520

日本深度學習市場按產品類型、應用、最終用戶產業、架構和地區分類，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個工作天內

價格
簡介目錄

2025年，日本深度學習市場規模達24.945億美元。展望未來，IMARC Group預測，到2034年，該市場規模將達到363.549億美元，2026年至2034年的複合年成長率（CAGR）為34.68%。來自社交媒體、物聯網設備和感測器等各種來源的數位資料快速成長，為深度學習演算法提供了豐富的資訊來源，從而推動了市場成長。

深度學習是人工智慧的一個分支，它模仿人腦的神經網路來解決複雜問題。它涉及訓練由多層相互連接的人工神經元組成的深度神經網路，使其能夠從數據中學習模式和表徵。這些網路擅長影像識別、語音辨識、自然語言處理，甚至自主決策等任務。深度學習的優點在於能夠自動發現和提取原始資料中的特徵，從而無需人工進行特徵工程。有效的模型訓練需要大規模資料集和高效能運算硬體，尤其是GPU。典型的深度學習架構包括用於影像分析的卷積類神經網路（CNN）和用於時間序列資料的循環神經網路（RNN）。深度學習的應用範圍非常廣泛，包括自動駕駛汽車、醫療診斷和建議系統。其持續發展和創新使機器能夠像人類一樣學習和決策，使其成為一項具有變革潛力的技術，並有望徹底改變各個產業。

日本深度學習市場趨勢：

日本深度學習市場的發展受到多種因素的共同驅動，這些因素共同改變了人工智慧（AI）的模式。首先，數據可用性的指數級成長，以及巨量資料分析的興起，為深度學習演算法的開發奠定了基礎。此外，GPU技術和雲端運算的創新不斷提升運算能力，使得以前所未有的規模和速度訓練深度神經網路成為可能。同時，醫療保健、金融和自動駕駛汽車等行業對深度學習的日益普及，也推動了對深度學習解決方案的需求激增。這種快速成長的需求不僅源自於其在提升決策和自動化方面的潛力，也源自於從海量資料集中提取有意義洞見的迫切需求。總而言之，豐富的數據、先進的運算能力、不斷擴展的應用領域以及便捷的工具，預計將共同推動日本深度學習市場的發展，並為該領域的持續成長和創新奠定基礎。

本報告解答的關鍵問題

  • 日本深度學習市場目前發展狀況如何？未來幾年又將如何發展？
  • 新冠疫情對日本深度學習市場產生了哪些影響？
  • 日本深度學習市場依產品類型分類的組成是怎樣的？
  • 日本深度學習市場按應用領域分類的組成是怎樣的？
  • 日本深度學習市場依終端用戶產業分類的組成是怎樣的？
  • 日本深度學習市場依架構分類的組成是怎樣的？
  • 日本深度學習市場價值鏈包含哪些階段？
  • 日本深度學習市場的主要促進因素和挑戰是什麼？
  • 日本深度學習市場的結構是怎麼樣的？主要企業有哪些？
  • 日本深度學習市場競爭有多激烈？

目錄

第1章：序言

第2章：調查範圍與調查方法

  • 調查目標
  • 相關利益者
  • 數據來源
  • 市場估值
  • 調查方法

第3章執行摘要

第4章：日本深度學習市場：簡介

  • 概述
  • 市場動態
  • 產業趨勢
  • 競爭資訊

第5章 日本深度學習市場概覽

  • 過去和當前的市場趨勢（2020-2025）
  • 市場預測（2026-2034）

第6章：日本深度學習市場：依產品類型分類

  • 軟體
  • 服務
  • 硬體

第7章 日本深度學習市場：依應用領域分類

  • 影像識別
  • 訊號識別
  • 資料探勘
  • 其他

第8章：日本深度學習市場：依最終用戶產業分類

  • 安全
  • 製造業
  • 零售
  • 車
  • 衛生保健
  • 農業
  • 其他

第9章：日本深度學習市場：依架構分類

  • RNN
  • CNN
  • DBN
  • DSN
  • GRU

第10章：日本深度學習市場：依地區分類

  • 關東地區
  • 關西、近畿地區
  • 中部地區
  • 九州和沖繩地區
  • 東北部地區
  • 中國地區
  • 北海道地區
  • 四國地區

第11章：日本深度學習市場：競爭格局

  • 概述
  • 市場結構
  • 市場公司定位
  • 關鍵成功策略
  • 競爭對手儀錶板
  • 企業估值象限

第12章主要企業概況

第13章：日本深度學習市場：產業分析

  • 促進因素、限制因素和機遇
  • 波特五力分析
  • 價值鏈分析

第14章附錄

簡介目錄
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