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Japan Deep Learning Market, By Offering (Hardware, Software, and Services), By Application (Image Recognition, Signal Recognition, and Data Mining), By End-User Industry (Healthcare, Retail, Automotive, Security, Manufacturing, and Others), By Architecture (RNN, CNN, DBN, DSN, and GRU), and By Region, Competition Forecast and Opportunities, 2027

Japan Deep Learning Market, By Offering (Hardware, Software, and Services), By Application (Image Recognition, Signal Recognition, and Data Mining), By End-User Industry (Healthcare, Retail, Automotive, Security, Manufacturing, and Others), By Architecture (RNN, CNN, DBN, DSN, and GRU), and By Region, Competition Forecast and Opportunities, 2027

The Japan deep learning market is projected to grow at a significant CAGR during the forecast period, 2023-2027. The market growth can be attributed to the increasing demand for deep learning from the manufacturing industry and supportive government policies. Besides, declining hardware costs is also contributing to the growth of the Japan deep learning market.
The Japanese government is promoting advanced technologies to boost productivity and reduce business losses. Besides, presence of well-developed technological infrastructure and the government's allocation of large funds for research and development activities facilitates the easy integration of advanced technology into existing infrastructure. Japan leads the world in industrial robot technology and intends to combine it with an open-source deep learning framework to improve results. Industrial robots are being used in the manufacturing industry to streamline and optimize operations.
The addition of deep learning technology enables the industrial robot to make accurate judgments during complex processes by learning from previous examples and can instantly share the knowledge with other existing industrial robots. Industrial robots can make informed decisions about where to pick up a block from a disorganized pile. Deep learning and image recognition with three-dimensional images Deep learning technology allow industrial robots to detect and prevent malfunctions in advance, resulting in increased productivity in the manufacturing industries.
The government-announced "Road to L4" project, which aims to increase the proliferation of advanced mobility services in the country, including level 4 autonomous driving, is also expected to create lucrative opportunities for Japan's deep learning market. In rural areas, older people are unable to drive vehicles with great precision, which increases the number of road accidents. In addition, the Ministry of Economy, Trade, and Industry (METI) intends to build 40 autonomous taxi test sites across the country by 2025. Autonomous vehicles, also known as self-driving cars, use deep learning technology to reduce road fatalities and improve consumer quality of life. The introduction of self-driving vehicles to support the growing geriatric population and the development of supportive road infrastructure are expected to propel Japan's deep learning market growth over the next five years.
The healthcare industry's increased adoption of advanced technologies to improve customer experience and efficiently maintain patient records is positively impacting market demand. The growing geriatric population, increased efforts and investments by the world's leading governments to improve elderly care services are accelerating the adoption of deep learning technology across the healthcare vertical. Deep learning technology can also be used to reduce time spent recognizing and categorizing patient belongings and optimizing the room allocation process. Increased penetration of telehealth and patient monitoring devices is expected to drive deep learning market growth in Japan over the next five years.
The Japan deep learning market is segmented on the basis of offering, application, end-user industry, architecture, company, and regional distribution. Based on application, the market is divided into image recognition, signal recognition, and data mining. The image recognition is projected to hold the largest share in the market during the forecast period, owing to the surge in demand for digital image processing, code recognition, facial recognition, pattern recognition, and optical character recognition.
Key players operating in the Japan deep learning market are Amazon Web Services (AWS), Google Inc., IBM Corporation, Intel Corporation, Microsoft Corporation, Preferred Networks, Abeja Inc., Cinnamon Inc., Ubie, and Ascent Robotics, among others.

Years considered for this report:

Historical Years: 2017-2020
Base Year: 2021
Estimated Year: 2022
Forecast Period: 2023–2027

Objective of the Study:
•To analyze the historical growth in the market size of the Japan deep learning from 2017 to 2021.
•To estimate and forecast the market size of Japan deep learning market from 2023 to 2027 and growth rate until 2027.
•To classify and forecast the Japan deep learning market based on offering, application, end user industry, architecture, region, and company.
•To identify the dominant region or segment in the Japan deep learning market.
•To identify drivers and challenges for the Japan deep learning market.
•To examine competitive developments such as expansions, new product launches, mergers & acquisitions, etc., in the Japan deep learning market.
•To identify and analyze the profiles of leading players operating in the Japan deep learning market.
•To identify key sustainable strategies adopted by market players in Japan deep learning market.

TechSci Research performed both primary as well as exhaustive secondary research for this study. Initially, TechSci Research sourced a list of manufacturers and service providers across the country. Subsequently, TechSci Research conducted primary research surveys with the identified companies. While interviewing, the respondents were also enquired about their competitors. Through this technique, TechSci Research could include the manufacturers and service providers who could not be identified due to the limitations of secondary research. TechSci Research analyzed the manufacturers, servcie providers, distribution channels and presence of all major players across the country.
TechSci Research calculated the market size of the Japan deep learning market using a top-down approach, wherein data for various end-user segments was recorded and forecast for the future years. TechSci Research sourced these values from the industry experts and company representatives and externally validated through analyzing historical data of these products and applications for getting an appropriate, overall market size. Various secondary sources such as company websites, news articles, press releases, company annual reports, investor presentations and financial reports were also studied by TechSci Research.

Key Target Audience:
•Market research and consulting firms
•Government bodies such as regulating authorities and policy makers
•Organizations, forums, and alliances
The study is useful in providing answers to several critical questions that are important for the industry stakeholders such as product manufacturers, service providers, suppliers and partners, end users, etc., besides allowing them in strategizing investments and capitalizing on market opportunities.

Report Scope:
In this report, Japan deep learning market has been segmented into following categories, in addition to the industry trends which have also been detailed below:
•Japan Deep Learning Market, By Offering:
oHardware
oSoftware
oServices
•Japan Deep Learning Market, By Application:
oImage Recognition
oSignal Recognition
oData Mining
•Japan Deep Learning Market, By End-User Industry:
oHealthcare
oRetail
oAutomotive
oSecurity
oManufacturing
oOthers
•Japan Deep Learning Market, By Architecture:
oRNN
oCNN
oDBN
oDSN
oGRU
•Japan Deep Learning Market, By Region:
oHokkaido & Tohoku
oKanto
oChubu
oKansai
oChugoku
oShikoku
oKyushu
Competitive Landscape

Company Profiles:Detailed analysis of the major companies present in Japan deep learning market.

Available Customizations:
With the given market data, TechSci Research offers customizations according to a company’s specific needs. The following customization options are available for the report:
Company Information
•Detailed analysis and profiling of additional market players (up to five).
Table of Contents

1.Product Overview
2.Research Methodology
3.Impact of COVID-19 on Japan Deep Learning Market
4.Executive Summary
5.Voice of Customers
5.1.1.Brand Awareness
5.1.2.Factors Considered while Selecting Supplier
5.1.3.Customer Satisfaction Level
5.1.4.Major Challenges Faced
6.Japan Deep Learning Market Outlook
6.1.Market Size & Forecast
6.1.1.By Value
6.2.Market Share & Forecast
6.2.1.By Offering (Hardware, Software, and Services)
6.2.2.By Application (Image Recognition, Signal Recognition, and Data Mining)
6.2.3.By End-User Industry (Healthcare, Retail, Automotive, Security, Manufacturing, and Others)
6.2.4.By Architecture (RNN, CNN, DBN, DSN, and GRU)
6.2.5.By Region
6.2.6.By Company (2021)
6.3.Product Market Map
7.Japan Deep Learning Hardware Market Outlook
7.1.Market Size & Forecast
7.1.1.By Value
7.2.Market Share & Forecast
7.2.1.By Application
7.2.2.By End-User Industry
7.2.3.By Architecture
7.2.4.By Region
8.Japan Deep Learning Software Market Outlook
8.1.Market Size & Forecast
8.1.1.By Value
8.2.Market Share & Forecast
8.2.1.By Application
8.2.2.By End-User Industry
8.2.3.By Architecture
8.2.4.By Region
9.Japan Deep Learning Services Market Outlook
9.1.Market Size & Forecast
9.1.1.By Value
9.2.Market Share & Forecast
9.2.1.By Application
9.2.2.By End-User Industry
9.2.3.By Architecture
9.2.4.By Region
10.Market Dynamics
10.1.Drivers
10.2.Challenges
11.Market Trends & Developments
12.Policy & Regulator Landscape
13.Japan Economic Profile
14.Company Profiles
14.1.Amazon Web Services (AWS)
14.2.Google Inc.
14.3.IBM Corporation
14.4.Intel Corporation
14.5.Microsoft Corporation
14.6.Preferred Networks
14.7.Abeja Inc.
14.8.Cinnamon Inc.
14.9.Ubie
14.10.Ascent Robotics
15.Strategic Recommendations

Report Title: Japan Deep Learning Market, By Offering (Hardware, Software, and Services), By Application (Image Recognition, Signal Recognition, and Data Mining), By End-User Industry (Healthcare, Retail, Automotive, Security, Manufacturing, and Others), By Architecture (RNN, CNN, DBN, DSN, and GRU), and By Region, Competition Forecast and Opportunities, 2027


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