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세계의 딥러닝 시장 규모, 점유율, 동향 분석 보고서 : 솔루션별, 용도별, 최종 용도별, 지역별, 부문별 예측(2025-2030년)

Deep Learning Market Size, Share & Trends Analysis Report By Solution, By Application (Image Recognition, Voice Recognition, Video Surveillance & Diagnostics, Data Mining), By End-use, By Region, And Segment Forecasts, 2025 - 2030

발행일: 2025년 01월 | 리서치사:

Grand View Research | 페이지 정보: 영문 118 Pages | 배송안내 : 2-10일 (영업일 기준)

※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

딥러닝 시장의 성장과 동향

Grand View Research, Inc.의 최신 보고서에 따르면, 세계 딥러닝 시장 규모는 2025-2030년간 31.8%의 연평균 복합 성장률(CAGR)을 나타내고, 2030년까지 5,267억 달러에 달할 것으로 예상됩니다.

딥러닝은 높은 연산 능력과 복잡한 데이터 기반 용도의 개선으로 인해 향후 몇 년동안 지속적인 모멘텀을 얻을 것으로 예상됩니다. 빅데이터 분석의 중요성이 부각되고 고객 중심 서비스에 인공지능(AI)이 도입되면서 예측 기간 동안 딥러닝 산업의 성장이 촉진될 것으로 예상됩니다.

AI는 최근 몇 년동안 빠르게 발전하여 기계가 인지 작업을 효율적으로 수행할 수 있게 되었습니다. 다양한 분야에서 AI가 채택되면서 머신러닝과 딥러닝 용도의 잠재적 기회가 많이 생겨나고 있습니다. 또한, 가상 비서와 같은 AI-as-a-service를 통해 소규모 조직에서도 대규모 설비 투자 없이도 딥러닝 용도에 필요한 AI 알고리즘을 구현할 수 있게 되었습니다. 또한, 대량의 데이터 가용성과 높은 컴퓨팅 성능이 요구됨에 따라 중소기업과 대기업은 딥러닝 기술에 많은 투자를 하고 있습니다.

딥러닝은 데이터가 충분히 정리되어 있지 않더라도 기계가 복잡한 문제를 해결할 수 있도록 합니다. 딥러닝 알고리즘은 작업을 반복적으로 실행하고, 매번 미세 조정하여 결과를 개선합니다. 따라서 기계가 작업을 더 많이 수행할수록 더 나은 결과를 얻을 수 있습니다. 그 결과, 대량의 비정형 데이터를 딥러닝 알고리즘을 통해 분석하여 보다 신뢰할 수 있는 의사결정 과정을 위한 관련 통찰력을 얻기 위해 더욱 확장할 수 있습니다. 예를 들어, 기업은 딥러닝 기술을 사용하여 산업 고찰, 소셜 미디어 대화, 특정 조직의 주가 사이에 있는 데이터 포인터를 파악할 수 있습니다.

이미지 인식과 음성 인식은 딥러닝 산업의 주요 응용 분야 중 하나이며, Amazon의 Alexa 가상 비서, Microsoft Cortana, Siri와 같은 일부 온라인 및 오프라인 서비스는 딥러닝을 활용하여 사람들과 대화하면서 언어 기술을 습득하고 있습니다. 페이스북과 구글은 이미지 분류 용도로 인지적 이미지 분석을 위한 딥러닝 기술을 구현했습니다. 이는 기업이 이미지와 관련된 적절한 결과와 자동 설명을 제공하는 데 도움이 됩니다.

또한, 딥러닝 알고리즘은 흑백 이미지를 컬러로 재현할 수 있으며, 이미지 컬러화 응용 분야에서 인상적이고 정확한 결과를 보여줍니다. 예를 들어, 2019년 6월 아마존은 Alexa에서 자연스러운 음성 경험을 제공하기 위해 Alexa Conversation이라는 새로운 딥러닝 모델을 도입했습니다.

딥러닝은 기술 채택률이 높기 때문에 벤더들에게 유리한 투자 기회를 제공합니다. 이에 따라 각 업체들은 딥러닝 산업에서 점유율을 확보하기 위한 전략적 노력의 하나로 제품 개발을 고려하고 있습니다. 최근에는 2020년 2월 구글(Google Inc.)이 트랜스포머(Transformer) 딥러닝 모델의 업데이트 버전인 Reformer의 출시를 발표했으며, 2020년 2월에는 Concentrix Corporation이 사이버 보안 용도의 딥러닝 알고리즘 툴을 발표했습니다.

딥러닝 시장 보고서 하이라이트

소프트웨어 부문이 딥러닝 산업을 주도하며 2024년 매출 점유율 46.64%를 차지했습니다. 개발자를 위한 소프트웨어 도구의 수는 지난 몇 년동안 크게 증가했습니다.
이미지 인식은 2024년 약 43.38%의 최대 시장 점유율을 차지했습니다. 딥러닝, 특히 CNN(Convolutional Neural Networks: 컨볼루션 신경망)으로 인해 이미지 인식의 정확도가 크게 향상되었습니다.
자동차 최종 용도 부문은 2024년 가장 큰 매출 점유율로 딥러닝 시장을 주도했습니다. 자율 주행 자동차는 엄청난 컴퓨팅 파워를 필요로 하는 획기적인 기술입니다.
북미 딥러닝 시장은 2024년 33.6%의 가장 높은 매출 점유율을 차지했습니다. 이러한 성장은 딥러닝이 데이터 분석과 업무 효율성을 향상시키는 다양한 부문, 특히 의료, 자동차, 소매업에서 딥러닝의 채택이 증가하고 있기 때문으로 분석됩니다.

딥러닝 시장 점유율, 지역별, 2024년/2030년
북미
- 미국
- 캐나다
- 멕시코
유럽
- 영국
- 독일
- 프랑스
아시아태평양
- 중국
- 일본
- 인도
- 한국
- 호주
라틴아메리카
- 브라질
중동 및 아프리카
- 아랍에미리트(UAE)
- 사우디아라비아
- 남아프리카공화국

제8장 경쟁 구도

기업 분류
기업의 시장 포지셔닝
참여 기업 개요
기업 히트맵 분석
전략 매핑
기업 개요/상장기업
- Advanced Micro Devices, Inc.
- ARM Ltd.
- Clarifai, Inc.
- Entilic
- Google, Inc.
- HyperVerge
- IBM Corporation
- Intel Corporation
- Microsoft Corporation
- NVIDIA Corporation

LSH 25.03.20

Deep Learning Market Growth & Trends:

The global deep learning market size is expected to reach USD 526.7 billion by 2030, registering a CAGR of 31.8% from 2025 to 2030, according to a new report by Grand View Research, Inc. Deep learning is expected to gain sustainable momentum in the coming years owing to its high computational ability and improved complex data-driven applications. The growing emphasis on big data analytics and the adoption of Artificial Intelligence (AI) in customer-centric services is expected to propel the growth of the deep learning industry over the forecast period.

AI has evolved rapidly in recent years, enabling machines to perform cognitive tasks effectively. The adoption of AI across various sectors has unlocked numerous potential opportunities for machine learning and deep learning applications. Furthermore, AI-as-a-service such as virtual assistants has allowed smaller organizations to implement AI algorithms required for deep learning applications without a large capital investment. Moreover, the availability of a large amount of data and the need for high computing power encourage SMEs and large enterprises to invest significantly in deep learning technology.

Deep learning allows the machine to solve complex problems even if the data is not well organized. A deep learning algorithm performs a task repeatedly, every time tweaking it to improve the outcomes. Thus, the more the task performed by the machines, the better will be the outcome. As a result, large amounts of unstructured data can be analyzed using deep learning algorithms and further deployed to obtain relevant insights for a more reliable decision-making process. For instance, organizations may use deep learning technology to unveil any data pointers between industry insights, social media conversation, and a stock price of a given organization.

Image and voice recognition are some of the leading applications in the deep learning industry. Several online and offline services such as Alexa virtual assistant by Amazon, Microsoft Cortana, and Siri use deep learning to acquire language skills while interacting with people. Facebook and Google have implemented deep learning technology for cognitive image analysis in their image classification application. It helps companies provide relevant results and automatic descriptions related to images.

Besides, deep learning algorithms can recreate a black-and-white image in color, offering impressive and accurate results in image colorization applications. For instance, In June 2019, Amazon introduced a new deep learning model called Alexa Conversations to create natural voice experiences on Alexa.

Deep learning offers lucrative investment opportunities for vendors due to the technology's high adoption rate. As a result, the companies consider product development as one of the strategic initiatives to capture the deep learning industry share. Recently, in February 2020, Google Inc. announced the launch of Reformer, an updated version of the transformer deep-learning model. In February 2020, Concentrix Corporation launched the deep learning algorithm tool for cybersecurity applications.

Deep Learning Market Report Highlights:

The software segment led the deep learning industry and accounted for a revenue share of 46.64% in 2024. The number of software tools for developers has grown significantly over the last few years.
Image recognition held the largest market share of around 43.38% in 2024. Deep learning, particularly through Convolutional Neural Networks (CNNs), has significantly improved image recognition accuracy.
The automotive end use segment led the deep learning market with the largest revenue share in 2024. The autonomous vehicle is a revolutionary technology that requires a massive amount of computation power.
North America deep learning market accounted for the highest revenue share of 33.6% in 2024. This growth is driven by increasing adoption across various sectors, particularly healthcare, automotive, and retail, where deep learning enhances data analysis and operational efficiency.

Chapter 1. Methodology and Scope

1.1. Market Segmentation and Scope
1.2. Research Methodology
- 1.2.1. Information Procurement
1.3. Information or Data Analysis
1.4. Methodology
1.5. Research Scope and Assumptions
1.6. Market Formulation & Validation
1.7. List of Data Sources

Chapter 2. Executive Summary

2.1. Market Outlook
2.2. Segment Outlook
2.3. Competitive Insights

Chapter 3. Deep Learning Market Variables, Trends, & Scope

3.1. Market Lineage Outlook
3.2. Market Dynamics
- 3.2.1. Market Driver Analysis
- 3.2.2. Market Restraint Analysis
- 3.2.3. Industry Challenge
3.3. Deep Learning Market Analysis Tools
- 3.3.1. Industry Analysis - Porter's
  - 3.3.1.1. Bargaining power of the suppliers
  - 3.3.1.2. Bargaining power of the buyers
  - 3.3.1.3. Threats of substitution
  - 3.3.1.4. Threats from new entrants
  - 3.3.1.5. Competitive rivalry
- 3.3.2. PESTEL Analysis
  - 3.3.2.1. Political landscape
  - 3.3.2.2. Economic and Social landscape
  - 3.3.2.3. Technological landscape

Chapter 4. Deep Learning Market: Solution Estimates & Trend Analysis

4.1. Segment Dashboard
4.2. Deep Learning Market: Solution Movement Analysis, 2024 & 2030 (USD Million)
4.3. Hardware
- 4.3.1. Hardware Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
  - 4.3.1.1. CPU
  - 4.3.1.2. GPU
  - 4.3.1.3. FPGA
  - 4.3.1.4. ASIC
4.4. Software
- 4.4.1. Software Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
4.5. Services
- 4.5.1. Services Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
  - 4.5.1.1. Installation services
  - 4.5.1.2. Integration services
  - 4.5.1.3. Maintenance & support services

Chapter 5. Deep Learning Market: Application Estimates & Trend Analysis

5.1. Segment Dashboard
5.2. Deep Learning Market: Application Movement Analysis, 2024 & 2030 (USD Million)
5.3. Image recognition
- 5.3.1. Image recognition Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
5.4. Voice recognition
- 5.4.1. Voice recognition Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
5.5. Video surveillance & diagnostics
- 5.5.1. Video surveillance & diagnostics Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
5.6. Data Mining
- 5.6.1. Data Mining Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)

Chapter 6. Deep Learning Market: End Use Estimates & Trend Analysis

6.1. Segment Dashboard
6.2. Deep Learning Market: End Use Movement Analysis, 2024 & 2030 (USD Million)
6.3. Automotive
- 6.3.1. Automotive Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
6.4. Aerospace & defense
- 6.4.1. Aerospace & defense Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
6.5. Healthcare
- 6.5.1. Healthcare Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
6.6. Retail
- 6.6.1. Retail Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)
6.7. Other
- 6.7.1. Other Market Revenue Estimates and Forecasts, 2018 - 2030 (USD Million)

Chapter 7. Deep Learning Market: Regional Estimates & Trend Analysis

7.1. Deep Learning Market Share, By Region, 2024 & 2030 (USD Million)
7.2. North America
- 7.2.1. North America Deep Learning Market Estimates and Forecasts, 2018 - 2030 (USD Million)
  - 7.2.1.1. North America Deep Learning Market Estimates and Forecasts, by Country, 2018 - 2030 (USD Million)
  - 7.2.1.2. North America Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.2.1.3. North America Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.2.1.4. North America Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.2.2. U.S.
  - 7.2.2.1. U.S. Deep Learning Market Estimates and Forecasts, 2018 - 2030 (USD Million)
  - 7.2.2.2. U.S. Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.2.2.3. U.S. Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.2.2.4. U.S. Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.2.3. Canada
  - 7.2.3.1. Canada Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.2.3.2. Canada Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.2.3.3. Canada Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.2.4. Mexico
  - 7.2.4.1. Mexico Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.2.4.2. Mexico Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.2.4.3. Mexico Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
7.3. Europe
- 7.3.1. Europe Deep Learning Market Estimates and Forecasts, 2018 - 2030 (USD Million)
  - 7.3.1.1. Europe Deep Learning Market Estimates and Forecasts, by Country, 2018 - 2030 (USD Million)
  - 7.3.1.2. Europe Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.3.1.3. Europe Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.3.1.4. Europe Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.3.2. UK
  - 7.3.2.1. UK Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.3.2.2. UK Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.3.2.3. UK Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.3.3. Germany
  - 7.3.3.1. Germany Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.3.3.2. Germany Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.3.3.3. Germany Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.3.4. France
  - 7.3.4.1. France Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.3.4.2. France Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.3.4.3. France Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
7.4. Asia Pacific
- 7.4.1. Asia Pacific Deep Learning Market Estimates and Forecasts, 2018 - 2030 (USD Million)
  - 7.4.1.1. Asia Pacific Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.4.1.2. Asia Pacific Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.4.1.3. Asia Pacific Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.4.2. China
  - 7.4.2.1. China Deep Learning Market Estimates and Forecasts, 2018 - 2030 (USD Million)
  - 7.4.2.2. China Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.4.2.3. China Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.4.2.4. China Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.4.3. Japan
  - 7.4.3.1. Japan Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.4.3.2. Japan Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.4.3.3. Japan Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.4.4. India
  - 7.4.4.1. India Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.4.4.2. India Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.4.4.3. India Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.4.5. South Korea
  - 7.4.5.1. South Korea Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.4.5.2. South Korea Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.4.5.3. South Korea Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.4.6. Australia
  - 7.4.6.1. Australia Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.4.6.2. Australia Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.4.6.3. Australia Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
7.5. Latin America
- 7.5.1. Latin America Deep Learning Market Estimates and Forecasts, 2018 - 2030 (USD Million)
  - 7.5.1.1. Latin America Deep Learning Market Estimates and Forecasts, by Country, 2018 - 2030 (USD Million)
  - 7.5.1.2. Latin America Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.5.1.3. Latin America Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.5.1.4. Latin America Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.5.2. Brazil
  - 7.5.2.1. Brazil Deep Learning Market Estimates and Forecasts, 2018 - 2030 (USD Million)
  - 7.5.2.2. Brazil Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.5.2.3. Brazil Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.5.2.4. Brazil Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
7.6. Middle East and Africa
- 7.6.1. Middle East and Africa Deep Learning Market Estimates and Forecasts, 2018 - 2030 (USD Million)
  - 7.6.1.1. Middle East and Africa Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.6.1.2. Middle East and Africa Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.6.1.3. Middle East and Africa Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.6.2. UAE
  - 7.6.2.1. UAE Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.6.2.2. UAE Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.6.2.3. UAE Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.6.3. KSA
  - 7.6.3.1. KSA Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.6.3.2. KSA Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.6.3.3. KSA Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)
- 7.6.4. South Africa
  - 7.6.4.1. South Africa Deep Learning Market Estimates and Forecasts, by Solution, 2018 - 2030 (USD Million)
  - 7.6.4.2. South Africa Deep Learning Market Estimates and Forecasts, by Application, 2018 - 2030 (USD Million)
  - 7.6.4.3. South Africa Deep Learning Market Estimates and Forecasts, by End Use, 2018 - 2030 (USD Million)

Chapter 8. Competitive Landscape

8.1. Company Categorization
8.2. Company Market Positioning
8.3. Participant's Overview
8.4. Financial Performance
8.5. Product Benchmarking
8.6. Company Heat Map Analysis
8.7. Strategy Mapping
8.8. Company Profiles/Listing
- 8.8.1. Advanced Micro Devices, Inc.
- 8.8.2. ARM Ltd.
- 8.8.3. Clarifai, Inc.
- 8.8.4. Entilic
- 8.8.5. Google, Inc.
- 8.8.6. HyperVerge
- 8.8.7. IBM Corporation
- 8.8.8. Intel Corporation
- 8.8.9. Microsoft Corporation
- 8.8.10. NVIDIA Corporation

02-2025-2992
(주말 및 공휴일 제외)

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※ 부가세 별도

세계의 딥러닝 시장 규모, 점유율, 동향 분석 보고서 : 솔루션별, 용도별, 최종 용도별, 지역별, 부문별 예측(2025-2030년)

Deep Learning Market Size, Share & Trends Analysis Report By Solution, By Application (Image Recognition, Voice Recognition, Video Surveillance & Diagnostics, Data Mining), By End-use, By Region, And Segment Forecasts, 2025 - 2030

딥러닝 시장의 성장과 동향

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제2장 주요 요약

제3장 딥러닝 시장 변수, 동향, 범위

제4장 딥러닝 시장 : 솔루션별, 추정 및 동향 분석

제5장 딥러닝 시장 : 용도별, 추정 및 동향 분석

제6장 딥러닝 시장 : 최종 용도별, 추정 및 동향 분석

제7장 딥러닝 시장 : 지역별, 추정 및 동향 분석