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市场调查报告书
商品编码
1746853

日本深度学习市场报告（按产品类型、应用、最终用途产业、架构和地区）2025-2033

Japan Deep Learning Market Report by Product Type, Application, End Use Industry, Architecture, and Region 2025-2033
出版日期: | 出版商: IMARC | 英文 118 Pages | 商品交期: 5-7个工作天内

价格
简介目录

2024年，日本深度学习市场规模达18.275亿美元。展望未来， IMARC Group预计到2033年，市场规模将达到299.86亿美元，2025-2033年期间的复合年增长率（CAGR）为36.5%。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日益增多，为深度学习演算法提供了丰富的资讯来源，推动着市场的发展。

深度学习是人工智慧的一个子集，它模仿人脑的神经网路来解决复杂的任务。它涉及训练深度神经网路（由许多相互连接的人工神经元层组成），以从资料中学习模式和表示。这些网路擅长图像和语音辨识、自然语言处理甚至自主决策等任务。深度学习的强大之处在于它能够自动从原始资料中发现和提取特征，从而无需手动进行特征工程。它依靠大型资料集和强大的运算硬体（尤其是 GPU）来有效地训练模型。流行的深度学习架构包括用于影像分析的捲积神经网路 (CNN) 和用于序列资料的循环神经网路 (RNN)。深度学习的应用非常广泛，包括自动驾驶汽车、医疗诊断、推荐系统等。它的不断发展和创新使其成为一项变革性技术，透过使机器能够像人类一样学习和决策，它有可能彻底改变各个行业。

日本深度学习市场趋势：

日本深度学习市场的发展受到一系列因素的共同推动，这些因素改变了人工智慧 (AI) 的模式。首先，资料可用性的指数级增长，加上巨量资料分析的兴起，为深度学习演算法的蓬勃发展铺平了道路。此外，在 GPU 技术和云端运算创新的推动下，运算能力的不断提升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。此外，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，也导致对深度学习解决方案的需求激增。这种蓬勃发展的需求不仅源于改进决策和自动化的潜力，也源于从海量资料集中提取有意义洞察的需求日益增长。总而言之，日本深度学习市场预计将受到资料丰富、运算能力强大、应用领域不断扩展以及工具便利性等因素的共同驱动，为该领域的持续成长和创新奠定基础。

日本深度学习市场区隔：

产品类型洞察：

  • 软体
  • 服务
  • 硬体

应用程式洞察：

  • 影像辨识
  • 讯号识别
  • 资料探勘
  • 其他的

最终用途行业洞察：

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

架构见解：

  • 循环神经网络
  • CNN
  • 资料库
  • 资料安全网络
  • 格鲁乌

竞争格局：

市场研究报告也对竞争格局进行了全面的分析。报告涵盖了市场结构、关键参与者定位、最佳制胜策略、竞争仪錶板和公司评估象限等竞争分析。此外，报告还提供了所有主要公司的详细资料。

本报告回答的关键问题：

  • 日本深度学习市场目前表现如何？未来几年会如何表现？
  • 新冠疫情对日本深度学习市场有何影响？
  • 日本深度学习市场依产品类型划分是怎样的？
  • 日本深度学习市场按应用划分是怎样的？
  • 日本深度学习市场依最终用途产业分類的状况如何？
  • 日本深度学习市场在架构上是如何分割的？
  • 日本深度学习市场的价值链分为哪些阶段？
  • 日本深度学习的关键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？主要参与者有哪些？
  • 日本深度学习市场的竞争程度如何？

本报告回答的关键问题：

  • 日本深度学习市场目前表现如何？未来几年会如何表现？
  • 新冠疫情对日本深度学习市场有何影响？
  • 日本深度学习市场依产品类型划分是怎样的？
  • 日本深度学习市场按应用划分是怎样的？
  • 日本深度学习市场依最终用途产业分類的状况如何？
  • 日本深度学习市场在架构上是如何分割的？
  • 日本深度学习市场的价值链分为哪些阶段？
  • 日本深度学习的关键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？主要参与者有哪些？
  • 日本深度学习市场的竞争程度如何？

目录

第一章：前言

第二章：范围与方法

  • 研究目标
  • 利害关係人
  • 资料来源
    • 主要来源
    • 次要来源
  • 市场评估
    • 自下而上的方法
    • 自上而下的方法
  • 预测方法

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
  • 竞争情报

第五章：日本深度学习市场模式

  • 历史与当前市场趋势（2019-2024）
  • 市场预测（2025-2033）

第六章：日本深度学习市场-细分：依产品类型

  • 软体
    • 概述
  • 服务
    • 概述
  • 硬体
    • 概述

第七章：日本深度学习市场-细分：依应用

  • 影像辨识
    • 概述
  • 讯号识别
    • 概述
  • 资料探勘
    • 概述
  • 其他的

第 8 章：日本深度学习市场 - 细分：按最终用途行业

  • 安全
    • 概述
  • 製造业
    • 概述
  • 零售
    • 概述
  • 汽车
    • 概述
  • 卫生保健
    • 概述
  • 农业
    • 概述
  • 其他的

第九章：日本深度学习市场-细分：依架构

  • 循环神经网络
    • 概述
  • CNN
    • 概述
  • 资料库
    • 概述
  • 资料安全网络
    • 概述
  • 格鲁乌
    • 概述

第十章：日本深度学习市场－竞争格局

  • 概述
  • 市场结构
  • 市场参与者定位
  • 最佳获胜策略
  • 竞争仪錶板
  • 公司评估象限

第 11 章：关键参与者简介

  • Company A
    • Business Overview
    • Services Offered
    • Business Strategies
    • SWOT Analysis
    • Major News and Events
  • Company B
    • Business Overview
    • Services Offered
    • Business Strategies
    • SWOT Analysis
    • Major News and Events
  • Company C
    • Business Overview
    • Services Offered
    • Business Strategies
    • SWOT Analysis
    • Major News and Events
  • Company D
    • Business Overview
    • Services Offered
    • Business Strategies
    • SWOT Analysis
    • Major News and Events
  • Company E
    • Business Overview
    • Services Offered
    • Business Strategies
    • SWOT Analysis
    • Major News and Events

第 12 章：日本深度学习市场 - 产业分析

  • 驱动因素、限制因素和机会
    • 概述
    • 驱动程式
    • 限制
    • 机会
  • 波特五力分析
    • 概述
    • 买家的议价能力
    • 供应商的议价能力
    • 竞争程度
    • 新进入者的威胁
    • 替代品的威胁
  • 价值链分析

第 13 章：附录

简介目录
Product Code: SR112025A19285

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

13 Appendix