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Global Deep Learning in Computer Vision Market - Industry Trends and Forecast to 2029

  • Semiconductors and Electronics
  • Upcoming Report
  • Dec 2021
  • Global
  • 350 Pages
  • No of Tables: 60
  • No of Figures: 220

Global Deep Learning in Computer Vision Market, By Hardware (Central Processing Unit (CPU), Graphics Processing Unit (GPU), Others), Solutions (Hardware, Software , Services), Application (Image recognition, Voice recognition, Others), End-User (Automotive, Healthcare , Others), Country (U.S., Canada, Mexico, Brazil, Argentina, Rest of South America, Germany, France, Italy, U.K., Belgium, Spain, Russia, Turkey, Netherlands, Switzerland, Rest of Europe, Japan, China, India, South Korea, Australia, Singapore, Malaysia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific, U.A.E, Saudi Arabia, Egypt, South Africa, Israel, Rest of Middle East and Africa)- Industry Trends and Forecast to 2029.

Deep Learning in Computer Vision Market Market Analysis and Insights of Deep Learning in Computer Vision Market

Deep learning in computer vision market is expected to gain market growth in the forecast period of 2022 to 2029. Data Bridge Market Research analyses the deep learning in computer vision market to exhibit a CAGR of 55.65% for the forecast period of 2022 to 2029.

Deep learning basically refers to an intense machine learning and artificial intelligence (AI) tool that generally indicates extraordinary execution in several fields and imitates the way humans gain certain types of knowledge. It includes face recognition and indexing, photo stylization or machine vision in self-driving cars.

The extensive improvements in fast information storage capacity is the vital factor escalating the market growth also increased computing power and parallelization and rising need for quality check and automation will emerge as the major factor driving market growth. Furthermore, the deep learning and technical advancements in hardware and software and rising adoption of 3D inspection system over conventional inspection systems are the factors that will further aggravate the market value. However, the lack of technical expertise and dearth of user awareness about rapidly changing computer vision technology act as a restraint for the market. The fact that most of the organizations might lack the appropriate resources and computing power to process huge amount of visual data, which might also impede the market’s overall growth within he forecasted period.

In addition to this, rising technological advancements and modernization are estimated to create new opportunities for growing the market within the forecast period. On the other hand, the disadvantages associated with cloud data storage, such as data breaches, data theft, and cloud data unavailability, are becoming more prevalent which can result as a challenge for the market.

 This deep learning in computer vision market report provides details of new recent developments, trade regulations, import export analysis, production analysis, value chain optimization, market share, impact of domestic and localized market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographical expansions, technological innovations in the market. To gain more info on deep learning in computer vision market contact Data Bridge Market Research for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

Global Deep Learning in Computer Vision Market Scope and Market Size

The deep learning in computer vision market is segmented on the basis of hardware, solutions, applications and end-user. The growth amongst the different segments helps you in attaining the knowledge related to the different growth factors expected to be prevalent throughout the market and formulate different strategies to help identify core application areas and the difference in your target market.

  • On the basis of hardware, the deep learning in computer vision market is segmented into central processing unit (CPU), graphics processing unit (GPU) and others
  • On the basis of solutions, the deep learning in computer vision market is segmented into hardware, software and services
  • Based on application, the deep learning in computer vision market is segmented into image recognition, voice recognition and others
  • The deep learning in computer vision market is also segmented on the basis of end-user into automotive, healthcare and others

 Deep Learning in Computer Vision Market Country Level Analysis

The deep learning in computer vision market is analyzed and market size, volume information is provided by hardware, solutions, applications and end-user as referenced above.

The countries covered in the deep learning in computer vision market report are U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, Israel, Egypt, South Africa, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.

North America region dominates the deep learning in computer vision market due to high adoption of image and pattern recognition, rising investments in artificial intelligence and neural networks in the region. Asia-Pacific region is projected to undergo substantial during the forecast period due to the various government’s strategic initiatives such as the governments are providing tech companies access to large datasets to build training models for computer vision applications.

The country section of the deep learning in computer vision market report also provides individual market impacting factors and changes in regulation in the market domestically that impacts the current and future trends of the market. Data points such as consumption volumes, production sites and volumes, import export analysis, price trend analysis, cost of raw materials, down-stream and upstream value chain analysis are some of the major pointers used to forecast the market scenario for individual countries. Also, presence and availability of global brands and their challenges faced due to large or scarce competition from local and domestic brands, impact of domestic tariffs and trade routes are considered while providing forecast analysis of the country data.

Competitive Landscape and Deep Learning in Computer Vision Market Share Analysis

The deep learning in computer vision market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies’ focus related to deep learning in computer vision market.

Some of the major players operating in the deep learning in computer vision market report are Accenture, IBM India Pvt Ltd, Circle Internet Services, Inc., Atlassian, Bitrise., CloudBees, Inc., Flexagon LLC., Infostretch Corporation, JetBrains s.r.o, Kainos., Micro Focus, MVTECH Software GmbH, Clarifai Inc., Tordivel AS., SICK AG, JAI A/S, CEVA Inc., Synopsys Inc., Microsoft, Puppet, Red Hat, Inc., Spirent Communications., and VMware, Inc., among others.


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Research Methodology:

Data collection and base year analysis are done using data collection modules with large sample sizes. The stage includes obtaining market information or related data through various sources and strategies. It includes examining and planning all the data acquired from the past in advance. It likewise envelops the examination of information inconsistencies seen across different information sources. The market data is analysed and estimated using market statistical and coherent models. Also, market share analysis and key trend analysis are the major success factors in the market report. To know more, please request an analyst call or drop down your inquiry.

The key research methodology used by DBMR research team is data triangulation which involves data mining, analysis of the impact of data variables on the market and primary (industry expert) validation. Data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Patent Analysis, Pricing Analysis, Company Market Share Analysis, Standards of Measurement, Global versus Regional and Vendor Share Analysis. To know more about the research methodology, drop in an inquiry to speak to our industry experts.

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