Global Deep Learning Neural Networks Market

Deep Learning Neural Networks Comprehensive Study by Application (Image Recognition, Natural Language Processing, Speech Recognition, Data Mining), Component (Hardware, Software, Services), End User (Banking, Financial Services & Insurance (BFSI), IT & Telecommunication, Healthcare, Retail, Automotive, Manufacturing, Aerospace & Defence, Security, Others) Players and Region - Global Market Outlook to 2028

Deep Learning Neural Networks Market by XX Submarkets | Forecast Years 2023-2028  

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  • Summary
  • Market Segments
  • Table of Content
  • List of Table & Figures
  • Players Profiled
About Deep Learning Neural Networks
The deep learning neural networks (DDNs) refers to the machine learning-based technology that is basically used for diagnosis- solving prediction, decision making, decision and problems based on a well-defined computational architecture and more. It helps to draw out a higher level of features from the raw input. The complex deep learning neural networks have multiple layers and each layer signifies the mathematical manipulation. The Deep Learning Neural Networks are used in various applications such as speech recognition, audio recognition, computer vision, and many others.

AttributesDetails
Study Period2018-2028
Base Year2022
UnitValue (USD Million)


The market is seeing moderate market players, by seeing huge growth in this market the key leading vendors are highly focusing on production technologies, efficiency enhancement, and product life. There is various growth opportunity in this market which is captured by leading players via tracking the ongoing process enhancement and huge investment in market growth strategies. Analyst at AMA Research estimates that United States Players will contribute the maximum growth to Global Deep Learning Neural Networks market throughout the forecasted period. Established and emerging Players should take a closer view at their existing organizations and reinvent traditional business and operating models to adapt to the future.

ALPHABET INC. (United States), IBM (United States), MICRON TECHNOLOGIES, INC. (United States), Neural Technologies Limited (United Kingdom), NEURODIMENSION, INC. (United States), NVIDIA CORPORATION (United States), SKYMIND INC (United States), SAMSUNG (South Korea), Qualcomm Technologies, Inc. (United States), Intel Corporation (United States), Amazon Web Services, Inc. (United States) and Microsoft Corporation (United States) are some of the key players that are part of study coverage. Additionally, the Players which are also part of the research coverage are Sensory Inc. (United States) and Xilinx Inc. (United States).

Segmentation Overview
AMA Research has segmented the market of Global Deep Learning Neural Networks market by , Application (Image Recognition, Natural Language Processing, Speech Recognition and Data Mining) and Region.



On the basis of geography, the market of Deep Learning Neural Networks has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, Taiwan, Australia, Rest of Asia-Pacific), Europe (Germany, France, Italy, United Kingdom, Netherlands, Rest of Europe), MEA (Middle East, Africa), North America (United States, Canada, Mexico). If we see Market by Component, the sub-segment i.e. Hardware will boost the Deep Learning Neural Networks market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth. If we see Market by End User, the sub-segment i.e. Banking will boost the Deep Learning Neural Networks market. Additionally, the rising demand from SMEs and various industry verticals gives enough cushion to market growth.

Influencing Trend:
Targeting specific industries

Market Growth Drivers:
Rapidly Increasing Digitization, Boosting the Global Deep Learning Neural Networks Market and Increased Demand of Cloud Computing for Businesses and Demand for Predictive Solutions and Image Recognition

Challenges:
Lack of Flexibility and Multitasking

Restraints:
Increasing Complexity Due to Complex Algorithm Used in Technology

Opportunities:
Cumulative Spending in Healthcare, Travel, Tourism, and Hospitality Industries and Increasing Awareness About the Deep Learning Neural Networks

Market Leaders and their expansionary development strategies
In October 2023, Google and Samsung announced a partnership to develop new AI chips for mobile devices. The partnership will combine Google's expertise in AI software with Samsung's expertise in semiconductor manufacturing. The two companies will work together to develop new chips that are optimized for AI applications, which could make it possible to run more sophisticated AI models on mobile devices.
In June 2023, Nvidia launched Grace Hopper, a supercomputer powered by Nvidia's H100 Tensor Cores. Grace Hopper is one of the most powerful supercomputers in the world and will be used to solve some of the world's most challenging problems.

About Approach
To evaluate and validate the market size various sources including primary and secondary analysis is utilized. AMA Research follows regulatory standards such as NAICS/SIC/ICB/TRCB, to have a better understanding of the market. The market study is conducted on basis of more than 200 companies dealing in the market regional as well as global areas with the purpose to understand the companies positioning regarding the market value, volume, and their market share for regional as well as global.

Further to bring relevance specific to any niche market we set and apply a number of criteria like Geographic Footprints, Regional Segments of Revenue, Operational Centres, etc. The next step is to finalize a team (In-House + Data Agencies) who then starts collecting C & D level executives and profiles, Industry experts, Opinion leaders, etc., and work towards appointment generation.

The primary research is performed by taking the interviews of executives of various companies dealing in the market as well as using the survey reports, research institute, and latest research reports. Meanwhile, the analyst team keeps preparing a set of questionnaires, and after getting the appointee list; the target audience is then tapped and segregated with various mediums and channels that are feasible for making connections that including email communication, telephonic, skype, LinkedIn Group & InMail, Community Forums, Community Forums, open Survey, SurveyMonkey, etc.

Report Objectives / Segmentation Covered

By Application
  • Image Recognition
  • Natural Language Processing
  • Speech Recognition
  • Data Mining
By Component
  • Hardware
  • Software
  • Services

By End User
  • Banking
  • Financial Services & Insurance (BFSI)
  • IT & Telecommunication
  • Healthcare
  • Retail
  • Automotive
  • Manufacturing
  • Aerospace & Defence
  • Security
  • Others

By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. Rapidly Increasing Digitization, Boosting the Global Deep Learning Neural Networks Market
      • 3.2.2. Increased Demand of Cloud Computing for Businesses and Demand for Predictive Solutions and Image Recognition
    • 3.3. Market Challenges
      • 3.3.1. Lack of Flexibility and Multitasking
    • 3.4. Market Trends
      • 3.4.1. Targeting specific industries
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global Deep Learning Neural Networks, by Application, Component, End User and Region (value and price ) (2017-2022)
    • 5.1. Introduction
    • 5.2. Global Deep Learning Neural Networks (Value)
      • 5.2.1. Global Deep Learning Neural Networks by: Application (Value)
        • 5.2.1.1. Image Recognition
        • 5.2.1.2. Natural Language Processing
        • 5.2.1.3. Speech Recognition
        • 5.2.1.4. Data Mining
      • 5.2.2. Global Deep Learning Neural Networks by: Component (Value)
        • 5.2.2.1. Hardware
        • 5.2.2.2. Software
        • 5.2.2.3. Services
      • 5.2.3. Global Deep Learning Neural Networks by: End User (Value)
        • 5.2.3.1. Banking
        • 5.2.3.2. Financial Services & Insurance (BFSI)
        • 5.2.3.3. IT & Telecommunication
        • 5.2.3.4. Healthcare
        • 5.2.3.5. Retail
        • 5.2.3.6. Automotive
        • 5.2.3.7. Manufacturing
        • 5.2.3.8. Aerospace & Defence
        • 5.2.3.9. Security
        • 5.2.3.10. Others
      • 5.2.4. Global Deep Learning Neural Networks Region
        • 5.2.4.1. South America
          • 5.2.4.1.1. Brazil
          • 5.2.4.1.2. Argentina
          • 5.2.4.1.3. Rest of South America
        • 5.2.4.2. Asia Pacific
          • 5.2.4.2.1. China
          • 5.2.4.2.2. Japan
          • 5.2.4.2.3. India
          • 5.2.4.2.4. South Korea
          • 5.2.4.2.5. Taiwan
          • 5.2.4.2.6. Australia
          • 5.2.4.2.7. Rest of Asia-Pacific
        • 5.2.4.3. Europe
          • 5.2.4.3.1. Germany
          • 5.2.4.3.2. France
          • 5.2.4.3.3. Italy
          • 5.2.4.3.4. United Kingdom
          • 5.2.4.3.5. Netherlands
          • 5.2.4.3.6. Rest of Europe
        • 5.2.4.4. MEA
          • 5.2.4.4.1. Middle East
          • 5.2.4.4.2. Africa
        • 5.2.4.5. North America
          • 5.2.4.5.1. United States
          • 5.2.4.5.2. Canada
          • 5.2.4.5.3. Mexico
    • 5.3. Global Deep Learning Neural Networks (Price)
  • 6. Deep Learning Neural Networks: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2022)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. ALPHABET INC. (United States)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. IBM (United States)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. MICRON TECHNOLOGIES, INC. (United States)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. Neural Technologies Limited (United Kingdom)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. NEURODIMENSION, INC. (United States)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. NVIDIA CORPORATION (United States)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. SKYMIND INC (United States)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. SAMSUNG (South Korea)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. Qualcomm Technologies, Inc. (United States)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Intel Corporation (United States)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
      • 6.4.11. Amazon Web Services, Inc. (United States)
        • 6.4.11.1. Business Overview
        • 6.4.11.2. Products/Services Offerings
        • 6.4.11.3. Financial Analysis
        • 6.4.11.4. SWOT Analysis
      • 6.4.12. Microsoft Corporation (United States)
        • 6.4.12.1. Business Overview
        • 6.4.12.2. Products/Services Offerings
        • 6.4.12.3. Financial Analysis
        • 6.4.12.4. SWOT Analysis
  • 7. Global Deep Learning Neural Networks Sale, by Application, Component, End User and Region (value and price ) (2023-2028)
    • 7.1. Introduction
    • 7.2. Global Deep Learning Neural Networks (Value)
      • 7.2.1. Global Deep Learning Neural Networks by: Application (Value)
        • 7.2.1.1. Image Recognition
        • 7.2.1.2. Natural Language Processing
        • 7.2.1.3. Speech Recognition
        • 7.2.1.4. Data Mining
      • 7.2.2. Global Deep Learning Neural Networks by: Component (Value)
        • 7.2.2.1. Hardware
        • 7.2.2.2. Software
        • 7.2.2.3. Services
      • 7.2.3. Global Deep Learning Neural Networks by: End User (Value)
        • 7.2.3.1. Banking
        • 7.2.3.2. Financial Services & Insurance (BFSI)
        • 7.2.3.3. IT & Telecommunication
        • 7.2.3.4. Healthcare
        • 7.2.3.5. Retail
        • 7.2.3.6. Automotive
        • 7.2.3.7. Manufacturing
        • 7.2.3.8. Aerospace & Defence
        • 7.2.3.9. Security
        • 7.2.3.10. Others
      • 7.2.4. Global Deep Learning Neural Networks Region
        • 7.2.4.1. South America
          • 7.2.4.1.1. Brazil
          • 7.2.4.1.2. Argentina
          • 7.2.4.1.3. Rest of South America
        • 7.2.4.2. Asia Pacific
          • 7.2.4.2.1. China
          • 7.2.4.2.2. Japan
          • 7.2.4.2.3. India
          • 7.2.4.2.4. South Korea
          • 7.2.4.2.5. Taiwan
          • 7.2.4.2.6. Australia
          • 7.2.4.2.7. Rest of Asia-Pacific
        • 7.2.4.3. Europe
          • 7.2.4.3.1. Germany
          • 7.2.4.3.2. France
          • 7.2.4.3.3. Italy
          • 7.2.4.3.4. United Kingdom
          • 7.2.4.3.5. Netherlands
          • 7.2.4.3.6. Rest of Europe
        • 7.2.4.4. MEA
          • 7.2.4.4.1. Middle East
          • 7.2.4.4.2. Africa
        • 7.2.4.5. North America
          • 7.2.4.5.1. United States
          • 7.2.4.5.2. Canada
          • 7.2.4.5.3. Mexico
    • 7.3. Global Deep Learning Neural Networks (Price)
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. Deep Learning Neural Networks: by Application(USD Million)
  • Table 2. Deep Learning Neural Networks Image Recognition , by Region USD Million (2017-2022)
  • Table 3. Deep Learning Neural Networks Natural Language Processing , by Region USD Million (2017-2022)
  • Table 4. Deep Learning Neural Networks Speech Recognition , by Region USD Million (2017-2022)
  • Table 5. Deep Learning Neural Networks Data Mining , by Region USD Million (2017-2022)
  • Table 6. Deep Learning Neural Networks: by Component(USD Million)
  • Table 7. Deep Learning Neural Networks Hardware , by Region USD Million (2017-2022)
  • Table 8. Deep Learning Neural Networks Software , by Region USD Million (2017-2022)
  • Table 9. Deep Learning Neural Networks Services , by Region USD Million (2017-2022)
  • Table 10. Deep Learning Neural Networks: by End User(USD Million)
  • Table 11. Deep Learning Neural Networks Banking , by Region USD Million (2017-2022)
  • Table 12. Deep Learning Neural Networks Financial Services & Insurance (BFSI) , by Region USD Million (2017-2022)
  • Table 13. Deep Learning Neural Networks IT & Telecommunication , by Region USD Million (2017-2022)
  • Table 14. Deep Learning Neural Networks Healthcare , by Region USD Million (2017-2022)
  • Table 15. Deep Learning Neural Networks Retail , by Region USD Million (2017-2022)
  • Table 16. Deep Learning Neural Networks Automotive , by Region USD Million (2017-2022)
  • Table 17. Deep Learning Neural Networks Manufacturing , by Region USD Million (2017-2022)
  • Table 18. Deep Learning Neural Networks Aerospace & Defence , by Region USD Million (2017-2022)
  • Table 19. Deep Learning Neural Networks Security , by Region USD Million (2017-2022)
  • Table 20. Deep Learning Neural Networks Others , by Region USD Million (2017-2022)
  • Table 21. South America Deep Learning Neural Networks, by Country USD Million (2017-2022)
  • Table 22. South America Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 23. South America Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 24. South America Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 25. Brazil Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 26. Brazil Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 27. Brazil Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 28. Argentina Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 29. Argentina Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 30. Argentina Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 31. Rest of South America Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 32. Rest of South America Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 33. Rest of South America Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 34. Asia Pacific Deep Learning Neural Networks, by Country USD Million (2017-2022)
  • Table 35. Asia Pacific Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 36. Asia Pacific Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 37. Asia Pacific Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 38. China Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 39. China Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 40. China Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 41. Japan Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 42. Japan Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 43. Japan Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 44. India Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 45. India Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 46. India Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 47. South Korea Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 48. South Korea Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 49. South Korea Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 50. Taiwan Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 51. Taiwan Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 52. Taiwan Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 53. Australia Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 54. Australia Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 55. Australia Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 56. Rest of Asia-Pacific Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 57. Rest of Asia-Pacific Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 58. Rest of Asia-Pacific Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 59. Europe Deep Learning Neural Networks, by Country USD Million (2017-2022)
  • Table 60. Europe Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 61. Europe Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 62. Europe Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 63. Germany Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 64. Germany Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 65. Germany Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 66. France Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 67. France Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 68. France Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 69. Italy Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 70. Italy Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 71. Italy Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 72. United Kingdom Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 73. United Kingdom Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 74. United Kingdom Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 75. Netherlands Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 76. Netherlands Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 77. Netherlands Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 78. Rest of Europe Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 79. Rest of Europe Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 80. Rest of Europe Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 81. MEA Deep Learning Neural Networks, by Country USD Million (2017-2022)
  • Table 82. MEA Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 83. MEA Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 84. MEA Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 85. Middle East Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 86. Middle East Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 87. Middle East Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 88. Africa Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 89. Africa Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 90. Africa Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 91. North America Deep Learning Neural Networks, by Country USD Million (2017-2022)
  • Table 92. North America Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 93. North America Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 94. North America Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 95. United States Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 96. United States Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 97. United States Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 98. Canada Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 99. Canada Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 100. Canada Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 101. Mexico Deep Learning Neural Networks, by Application USD Million (2017-2022)
  • Table 102. Mexico Deep Learning Neural Networks, by Component USD Million (2017-2022)
  • Table 103. Mexico Deep Learning Neural Networks, by End User USD Million (2017-2022)
  • Table 104. Company Basic Information, Sales Area and Its Competitors
  • Table 105. Company Basic Information, Sales Area and Its Competitors
  • Table 106. Company Basic Information, Sales Area and Its Competitors
  • Table 107. Company Basic Information, Sales Area and Its Competitors
  • Table 108. Company Basic Information, Sales Area and Its Competitors
  • Table 109. Company Basic Information, Sales Area and Its Competitors
  • Table 110. Company Basic Information, Sales Area and Its Competitors
  • Table 111. Company Basic Information, Sales Area and Its Competitors
  • Table 112. Company Basic Information, Sales Area and Its Competitors
  • Table 113. Company Basic Information, Sales Area and Its Competitors
  • Table 114. Company Basic Information, Sales Area and Its Competitors
  • Table 115. Company Basic Information, Sales Area and Its Competitors
  • Table 116. Deep Learning Neural Networks: by Application(USD Million)
  • Table 117. Deep Learning Neural Networks Image Recognition , by Region USD Million (2023-2028)
  • Table 118. Deep Learning Neural Networks Natural Language Processing , by Region USD Million (2023-2028)
  • Table 119. Deep Learning Neural Networks Speech Recognition , by Region USD Million (2023-2028)
  • Table 120. Deep Learning Neural Networks Data Mining , by Region USD Million (2023-2028)
  • Table 121. Deep Learning Neural Networks: by Component(USD Million)
  • Table 122. Deep Learning Neural Networks Hardware , by Region USD Million (2023-2028)
  • Table 123. Deep Learning Neural Networks Software , by Region USD Million (2023-2028)
  • Table 124. Deep Learning Neural Networks Services , by Region USD Million (2023-2028)
  • Table 125. Deep Learning Neural Networks: by End User(USD Million)
  • Table 126. Deep Learning Neural Networks Banking , by Region USD Million (2023-2028)
  • Table 127. Deep Learning Neural Networks Financial Services & Insurance (BFSI) , by Region USD Million (2023-2028)
  • Table 128. Deep Learning Neural Networks IT & Telecommunication , by Region USD Million (2023-2028)
  • Table 129. Deep Learning Neural Networks Healthcare , by Region USD Million (2023-2028)
  • Table 130. Deep Learning Neural Networks Retail , by Region USD Million (2023-2028)
  • Table 131. Deep Learning Neural Networks Automotive , by Region USD Million (2023-2028)
  • Table 132. Deep Learning Neural Networks Manufacturing , by Region USD Million (2023-2028)
  • Table 133. Deep Learning Neural Networks Aerospace & Defence , by Region USD Million (2023-2028)
  • Table 134. Deep Learning Neural Networks Security , by Region USD Million (2023-2028)
  • Table 135. Deep Learning Neural Networks Others , by Region USD Million (2023-2028)
  • Table 136. South America Deep Learning Neural Networks, by Country USD Million (2023-2028)
  • Table 137. South America Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 138. South America Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 139. South America Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 140. Brazil Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 141. Brazil Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 142. Brazil Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 143. Argentina Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 144. Argentina Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 145. Argentina Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 146. Rest of South America Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 147. Rest of South America Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 148. Rest of South America Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 149. Asia Pacific Deep Learning Neural Networks, by Country USD Million (2023-2028)
  • Table 150. Asia Pacific Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 151. Asia Pacific Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 152. Asia Pacific Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 153. China Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 154. China Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 155. China Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 156. Japan Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 157. Japan Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 158. Japan Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 159. India Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 160. India Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 161. India Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 162. South Korea Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 163. South Korea Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 164. South Korea Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 165. Taiwan Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 166. Taiwan Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 167. Taiwan Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 168. Australia Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 169. Australia Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 170. Australia Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 171. Rest of Asia-Pacific Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 172. Rest of Asia-Pacific Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 173. Rest of Asia-Pacific Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 174. Europe Deep Learning Neural Networks, by Country USD Million (2023-2028)
  • Table 175. Europe Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 176. Europe Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 177. Europe Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 178. Germany Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 179. Germany Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 180. Germany Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 181. France Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 182. France Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 183. France Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 184. Italy Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 185. Italy Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 186. Italy Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 187. United Kingdom Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 188. United Kingdom Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 189. United Kingdom Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 190. Netherlands Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 191. Netherlands Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 192. Netherlands Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 193. Rest of Europe Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 194. Rest of Europe Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 195. Rest of Europe Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 196. MEA Deep Learning Neural Networks, by Country USD Million (2023-2028)
  • Table 197. MEA Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 198. MEA Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 199. MEA Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 200. Middle East Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 201. Middle East Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 202. Middle East Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 203. Africa Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 204. Africa Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 205. Africa Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 206. North America Deep Learning Neural Networks, by Country USD Million (2023-2028)
  • Table 207. North America Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 208. North America Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 209. North America Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 210. United States Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 211. United States Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 212. United States Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 213. Canada Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 214. Canada Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 215. Canada Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 216. Mexico Deep Learning Neural Networks, by Application USD Million (2023-2028)
  • Table 217. Mexico Deep Learning Neural Networks, by Component USD Million (2023-2028)
  • Table 218. Mexico Deep Learning Neural Networks, by End User USD Million (2023-2028)
  • Table 219. Research Programs/Design for This Report
  • Table 220. Key Data Information from Secondary Sources
  • Table 221. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global Deep Learning Neural Networks: by Application USD Million (2017-2022)
  • Figure 5. Global Deep Learning Neural Networks: by Component USD Million (2017-2022)
  • Figure 6. Global Deep Learning Neural Networks: by End User USD Million (2017-2022)
  • Figure 7. South America Deep Learning Neural Networks Share (%), by Country
  • Figure 8. Asia Pacific Deep Learning Neural Networks Share (%), by Country
  • Figure 9. Europe Deep Learning Neural Networks Share (%), by Country
  • Figure 10. MEA Deep Learning Neural Networks Share (%), by Country
  • Figure 11. North America Deep Learning Neural Networks Share (%), by Country
  • Figure 12. Global Deep Learning Neural Networks share by Players 2022 (%)
  • Figure 13. Global Deep Learning Neural Networks share by Players (Top 3) 2022(%)
  • Figure 14. Global Deep Learning Neural Networks share by Players (Top 5) 2022(%)
  • Figure 15. BCG Matrix for key Companies
  • Figure 16. ALPHABET INC. (United States) Revenue, Net Income and Gross profit
  • Figure 17. ALPHABET INC. (United States) Revenue: by Geography 2022
  • Figure 18. IBM (United States) Revenue, Net Income and Gross profit
  • Figure 19. IBM (United States) Revenue: by Geography 2022
  • Figure 20. MICRON TECHNOLOGIES, INC. (United States) Revenue, Net Income and Gross profit
  • Figure 21. MICRON TECHNOLOGIES, INC. (United States) Revenue: by Geography 2022
  • Figure 22. Neural Technologies Limited (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 23. Neural Technologies Limited (United Kingdom) Revenue: by Geography 2022
  • Figure 24. NEURODIMENSION, INC. (United States) Revenue, Net Income and Gross profit
  • Figure 25. NEURODIMENSION, INC. (United States) Revenue: by Geography 2022
  • Figure 26. NVIDIA CORPORATION (United States) Revenue, Net Income and Gross profit
  • Figure 27. NVIDIA CORPORATION (United States) Revenue: by Geography 2022
  • Figure 28. SKYMIND INC (United States) Revenue, Net Income and Gross profit
  • Figure 29. SKYMIND INC (United States) Revenue: by Geography 2022
  • Figure 30. SAMSUNG (South Korea) Revenue, Net Income and Gross profit
  • Figure 31. SAMSUNG (South Korea) Revenue: by Geography 2022
  • Figure 32. Qualcomm Technologies, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 33. Qualcomm Technologies, Inc. (United States) Revenue: by Geography 2022
  • Figure 34. Intel Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 35. Intel Corporation (United States) Revenue: by Geography 2022
  • Figure 36. Amazon Web Services, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 37. Amazon Web Services, Inc. (United States) Revenue: by Geography 2022
  • Figure 38. Microsoft Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 39. Microsoft Corporation (United States) Revenue: by Geography 2022
  • Figure 40. Global Deep Learning Neural Networks: by Application USD Million (2023-2028)
  • Figure 41. Global Deep Learning Neural Networks: by Component USD Million (2023-2028)
  • Figure 42. Global Deep Learning Neural Networks: by End User USD Million (2023-2028)
  • Figure 43. South America Deep Learning Neural Networks Share (%), by Country
  • Figure 44. Asia Pacific Deep Learning Neural Networks Share (%), by Country
  • Figure 45. Europe Deep Learning Neural Networks Share (%), by Country
  • Figure 46. MEA Deep Learning Neural Networks Share (%), by Country
  • Figure 47. North America Deep Learning Neural Networks Share (%), by Country
List of companies from research coverage that are profiled in the study
  • ALPHABET INC. (United States)
  • IBM (United States)
  • MICRON TECHNOLOGIES, INC. (United States)
  • Neural Technologies Limited (United Kingdom)
  • NEURODIMENSION, INC. (United States)
  • NVIDIA CORPORATION (United States)
  • SKYMIND INC (United States)
  • SAMSUNG (South Korea)
  • Qualcomm Technologies, Inc. (United States)
  • Intel Corporation (United States)
  • Amazon Web Services, Inc. (United States)
  • Microsoft Corporation (United States)
Additional players considered in the study are as follows:
Sensory Inc. (United States) , Xilinx Inc. (United States)
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Key Highlights of Report


Dec 2023 180 Pages 69 Tables Base Year: 2022 Coverage: 15+ Companies; 18 Countries

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Global Deep Learning Neural Networks Market Quantitative research analysis
Global Deep Learning Neural Networks Market Qualitative Industry Analysis
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Frequently Asked Questions (FAQ):

The standard version of the report profiles players such as ALPHABET INC. (United States), IBM (United States), MICRON TECHNOLOGIES, INC. (United States), Neural Technologies Limited (United Kingdom), NEURODIMENSION, INC. (United States), NVIDIA CORPORATION (United States), SKYMIND INC (United States), SAMSUNG (South Korea), Qualcomm Technologies, Inc. (United States), Intel Corporation (United States), Amazon Web Services, Inc. (United States) and Microsoft Corporation (United States) etc.
The Study can be customized subject to feasibility and data availability. Please connect with our sales representative for further information.
"Targeting specific industries" is seen as one of major influencing trends for Deep Learning Neural Networks Market during projected period 2022-2028.
The Deep Learning Neural Networks market study includes a random mix of players, including both market leaders and some top growing emerging players. Connect with our sales executive to get a complete company list in our research coverage.

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