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市場調査レポート
商品コード
1746853
日本のディープラーニング市場レポート：製品タイプ、用途、最終用途産業、アーキテクチャ、地域別、2025年～2033年Japan Deep Learning Market Report by Product Type, Application, End Use Industry, Architecture, and Region 2025-2033 |
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| 日本のディープラーニング市場レポート：製品タイプ、用途、最終用途産業、アーキテクチャ、地域別、2025年～2033年 |
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出版日: 2025年06月02日
発行: IMARC
ページ情報: 英文 118 Pages
納期: 5～7営業日
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- 全表示
- 概要
- 目次
日本のディープラーニング市場規模は2024年に18億2,750万米ドルに達しました。今後、IMARC Groupは、同市場が2033年までに299億8,600万米ドルに達し、2025年から2033年にかけて36.5%の成長率（CAGR）を示すと予測しています。日本ディープラーニングアルゴリズムに豊富な情報源を提供するソーシャルメディア、IoTデバイス、センサーなど、さまざまなソースからのデジタルデータの急増が市場を牽引しています。
本レポートで扱う主な質問
- 日本のディープラーニング市場はこれまでどのように推移し、今後どのように推移するのか？
- COVID-19が日本のディープラーニング市場に与えた影響は？
- 日本のディープラーニング市場の製品タイプ別区分は？
- 日本のディープラーニング市場の用途別区分は？
- 日本のディープラーニング市場の最終用途産業別の区分は？
- 日本のディープラーニング市場のアーキテクチャ別内訳は？
- 日本のディープラーニング市場のバリューチェーンにおける各ステージとは？
- 日本のディープラーニングの主要な促進要因と課題は？
- 日本のディープラーニング市場の構造と主要プレーヤーは？
- 日本のディープラーニング市場における競合の程度は？
目次
第1章 序文
第2章 調査範囲と調査手法
- 調査の目的
- ステークホルダー
- データソース
- 市場推定
- 調査手法
第3章 エグゼクティブサマリー
第4章 日本ディープラーニング市場-イントロダクション
- 概要
- 市場力学
- 業界動向
- 競合情報
第5章 日本ディープラーニング市場情勢
- 過去および現在の市場動向（2019～2024年）
- 市場予測（2025～2033年）
第6章 日本のディープラーニング市場- 製品タイプ別の内訳
- ソフトウェア
- サービス
- ハードウェア
第7章 日本のディープラーニング市場- 用途別の内訳
- 画像認識
- 信号認識
- データマイニング
- その他
第8章 日本のディープラーニング市場- 最終用途産業別の内訳
- セキュリティ
- 製造
- 小売り
- 自動車
- ヘルスケア
- 農業
- その他
第9章 日本のディープラーニング市場- アーキテクチャ別の内訳
- RNN
- CNN
- DBN
- DSN
- GRU
第10章 日本のディープラーニング市場- 競合情勢
- 概要
- 市場構造
- 市場企業のポジショニング
- 主要成功戦略
- 競合ダッシュボード
- 企業評価象限
第11章 主要企業のプロファイル
第12章 日本のディープラーニング市場- 業界分析
- 促進要因・抑制要因・機会
- ポーターのファイブフォース分析
- バリューチェーン分析
第13章 付録
Japan deep learning market size reached USD 1,827.5 Million in 2024. Looking forward, IMARC Group expects the market to reach USD 29,986.0 Million by 2033, exhibiting a growth rate (CAGR) of 36.5% during 2025-2033. 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.
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:
- Software
- Services
- Hardware
Application Insights:
- Image Recognition
- Signal Recognition
- Data Mining
- Others
End Use Industry Insights:
- Security
- Manufacturing
- Retail
- Automotive
- Healthcare
- Agriculture
- Others
Architecture Insights:
- RNN
- CNN
- DBN
- DSN
- GRU
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 (2019-2024)
- 5.2 Market Forecast (2025-2033)
6 Japan Deep Learning Market - Breakup by Product Type
- 6.1 Software
- 6.1.1 Overview
- 6.1.2 Historical and Current Market Trends (2019-2024)
- 6.1.3 Market Forecast (2025-2033)
- 6.2 Services
- 6.2.1 Overview
- 6.2.2 Historical and Current Market Trends (2019-2024)
- 6.2.3 Market Forecast (2025-2033)
- 6.3 Hardware
- 6.3.1 Overview
- 6.3.2 Historical and Current Market Trends (2019-2024)
- 6.3.3 Market Forecast (2025-2033)
7 Japan Deep Learning Market - Breakup by Application
- 7.1 Image Recognition
- 7.1.1 Overview
- 7.1.2 Historical and Current Market Trends (2019-2024)
- 7.1.3 Market Forecast (2025-2033)
- 7.2 Signal Recognition
- 7.2.1 Overview
- 7.2.2 Historical and Current Market Trends (2019-2024)
- 7.2.3 Market Forecast (2025-2033)
- 7.3 Data Mining
- 7.3.1 Overview
- 7.3.2 Historical and Current Market Trends (2019-2024)
- 7.3.3 Market Forecast (2025-2033)
- 7.4 Others
- 7.4.1 Historical and Current Market Trends (2019-2024)
- 7.4.2 Market Forecast (2025-2033)
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 (2019-2024)
- 8.1.3 Market Forecast (2025-2033)
- 8.2 Manufacturing
- 8.2.1 Overview
- 8.2.2 Historical and Current Market Trends (2019-2024)
- 8.2.3 Market Forecast (2025-2033)
- 8.3 Retail
- 8.3.1 Overview
- 8.3.2 Historical and Current Market Trends (2019-2024)
- 8.3.3 Market Forecast (2025-2033)
- 8.4 Automotive
- 8.4.1 Overview
- 8.4.2 Historical and Current Market Trends (2019-2024)
- 8.4.3 Market Forecast (2025-2033)
- 8.5 Healthcare
- 8.5.1 Overview
- 8.5.2 Historical and Current Market Trends (2019-2024)
- 8.5.3 Market Forecast (2025-2033)
- 8.6 Agriculture
- 8.6.1 Overview
- 8.6.2 Historical and Current Market Trends (2019-2024)
- 8.6.3 Market Forecast (2025-2033)
- 8.7 Others
- 8.7.1 Historical and Current Market Trends (2019-2024)
- 8.7.2 Market Forecast (2025-2033)
9 Japan Deep Learning Market - Breakup by Architecture
- 9.1 RNN
- 9.1.1 Overview
- 9.1.2 Historical and Current Market Trends (2019-2024)
- 9.1.3 Market Forecast (2025-2033)
- 9.2 CNN
- 9.2.1 Overview
- 9.2.2 Historical and Current Market Trends (2019-2024)
- 9.2.3 Market Forecast (2025-2033)
- 9.3 DBN
- 9.3.1 Overview
- 9.3.2 Historical and Current Market Trends (2019-2024)
- 9.3.3 Market Forecast (2025-2033)
- 9.4 DSN
- 9.4.1 Overview
- 9.4.2 Historical and Current Market Trends (2019-2024)
- 9.4.3 Market Forecast (2025-2033)
- 9.5 GRU
- 9.5.1 Overview
- 9.5.2 Historical and Current Market Trends (2019-2024)
- 9.5.3 Market Forecast (2025-2033)
10 Japan Deep Learning Market - Competitive Landscape
- 10.1 Overview
- 10.2 Market Structure
- 10.3 Market Player Positioning
- 10.4 Top Winning Strategies
- 10.5 Competitive Dashboard
- 10.6 Company Evaluation Quadrant
11 Profiles of Key Players
- 11.1 Company A
- 11.1.1 Business Overview
- 11.1.2 Services Offered
- 11.1.3 Business Strategies
- 11.1.4 SWOT Analysis
- 11.1.5 Major News and Events
- 11.2 Company B
- 11.2.1 Business Overview
- 11.2.2 Services Offered
- 11.2.3 Business Strategies
- 11.2.4 SWOT Analysis
- 11.2.5 Major News and Events
- 11.3 Company C
- 11.3.1 Business Overview
- 11.3.2 Services Offered
- 11.3.3 Business Strategies
- 11.3.4 SWOT Analysis
- 11.3.5 Major News and Events
- 11.4 Company D
- 11.4.1 Business Overview
- 11.4.2 Services Offered
- 11.4.3 Business Strategies
- 11.4.4 SWOT Analysis
- 11.4.5 Major News and Events
- 11.5 Company E
- 11.5.1 Business Overview
- 11.5.2 Services Offered
- 11.5.3 Business Strategies
- 11.5.4 SWOT Analysis
- 11.5.5 Major News and Events
12 Japan Deep Learning Market - Industry Analysis
- 12.1 Drivers, Restraints, and Opportunities
- 12.1.1 Overview
- 12.1.2 Drivers
- 12.1.3 Restraints
- 12.1.4 Opportunities
- 12.2 Porters Five Forces Analysis
- 12.2.1 Overview
- 12.2.2 Bargaining Power of Buyers
- 12.2.3 Bargaining Power of Suppliers
- 12.2.4 Degree of Competition
- 12.2.5 Threat of New Entrants
- 12.2.6 Threat of Substitutes
- 12.3 Value Chain Analysis
