Deep Learning in Computer Vision Market Competitive Projected To Grow At A CAGR Of 55.7% By 2026 With Accenture, appLariat, Appveyor Systems Inc., Atlassian, Bitrise, CA Technologies, Chef Software, CircleCI, Clarive, Cloudbees, Electric Cloud

This report is divided into production facilities, types, applications and regions. Deep Learning in Computer Vision's market report shares details of upstream raw materials, downstream demand and value for production with some important factors that could potentially lead to market growth.
Some of the market's prominent trends include improved profitability as a result of the goal, the introduction of the maintenance-as - a-service model in industries, increased demand in the industry and opportunities for growth and investment.

Some of the important points covered in this report are a market overview, competitive analysis, competition by manufacturers, new players, suppliers and vendors, regional output, type and application, volume and shares, sales value and product price, sales revenue and gross margin.
The report includes the CAGR figures for the base year 2017 in the historical year 2016 and the forecast year 2018-2025 for the Deep Learning in Computer Vision market, which subsequently affects the industry.

The Global Deep Learning in Computer Vision Market accounted for USD 7.8 billion in 2017 and is projected to grow at a CAGR of 55.7% the forecast period of 2018 to 2025. The upcoming market report contains data for historic years 2016, the base year of calculation is 2017 and the forecast period is 2018 to 2025.

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Global Deep Learning in Computer Vision Market By Solutions (Hardware, Software , Services), By Hardware (Central Processing Unit (CPU), Graphics Processing Unit (GPU), Others), By Application (Image recognition, Voice recognition ,Others), By End-user (Automotive, Healthcare , Others) ,By Geographical Segments (North America, South America, Europe, Asia-Pacific, Middle East and Africa)- Industry Trends and Forecast to 2025

Key Players:

The renowned players in deep learning in computer vision market are Accenture, Applariat, Appveyor, Atlassian, Bitrise, CA Technologies, Chef Software, Circleci, Clarive, Cloudbees, Electric Cloud, Flexagon, Heroku, IBM, Infostretch, Jetbrains, Kainos, Micro Focus, Microsoft, Puppet Enterprise, Red Hat, Shippable, Spirent, VMware, Wipro and Xebialabs among others.

Market Drivers and Restraints:

• Rapid improvements in fast information storage capacity.

• High computing power and parallelization.

• Need for quality check and automation is increasing.

• Lack of technical expertise.

• Lack of user awareness about rapidly changing computer vision technology for deep learning.

For a pervasive understanding of the market, business strategies and latest developments of the vital players accompanied with co-development deals and market size have also been enclosed. Briefly citing, their revenue share, contact information and meticulous SWOT analysis is available. The regions which have been studied in depth are North America, Europe, Asia Pacific, Middle East & Africa and Latin America. This helps gain better idea about the spread of this particular market in respective regions.

The report takes a close and analytical look at the various companies that strive for a higher share of the Deep Learning in Computer Vision Market. Data on the leading and fastest-growing segments along with what drives them has been given.

This report implements a balanced mix of primary and secondary research methodologies for its analysis. The market is segmented on the basis of key criteria.

A bird’s eye view of the Deep Learning in Computer Vision Industry made available in the report helps readers to understand the key drivers, restraints, challenges, and opportunities that are shaping the Deep Learning in Computer Vision market. Furthermore, the report evaluates challenges experienced from buyers and sellers side.

TABLE OF CONTENTS

PART 01: EXECUTIVE SUMMARY

PART 02: SCOPE OF THE REPORT

PART 03: RESEARCH METHODOLOGY

PART 04: MARKET LANDSCAPE

• Market ecosystem
• Market characteristics
• Market segmentation analysis

PART 05: PIPELINE ANALYSIS

• Pipeline analysis

PART 06: MARKET SIZING

• Market definition
• Market sizing
• Market size and forecast

PART 07: FIVE FORCES ANALYSIS

• Bargaining power of buyers
• Bargaining power of suppliers
• Threat of new entrants
• Threat of substitutes
• Threat of rivalry
• Market condition

PART 08: MARKET SEGMENTATION

• Segmentation
• Comparison
• Market opportunity

PART 09: CUSTOMER LANDSCAPE

PART 10: REGIONAL LANDSCAPE

• Geographical segmentation
• Regional comparison
• North America
• South America
• Europe
• MEA
• APAC
• Market opportunity

PART 11: DECISION FRAMEWORK

PART 12: DRIVERS AND CHALLENGES

• Market drivers
• Market challenges

PART 13: MARKET TRENDS

PART 14: VENDOR LANDSCAPE

• Overview
• Landscape disruption

PART 15: VENDOR ANALYSIS

• Vendors covered
• Vendor classification
• Market positioning of vendors

PART 16: APPENDIX

• List of abbreviations

Key Highlights of Report

• Overview of key market forces propelling and restraining market growth

• Offers a clear understanding of the competitive landscape and key product segments

• An analysis of strategies of major competitors

• Detailed analyses of industry trends

• A well-defined technological growth map with an impact-analysis

• Provides profiles of major competitors of the market.

• Details of their operations, product and services.

• Recent developments and key financial metrics.

Market Definition:

Deep learning is an intense machine learning tool that indicates extraordinary execution in numerous fields. One of the best accomplishments of deep learning is protest acknowledgment with Convolutional Neural Networks (CNNs). CNNs’ principle control originates from gaining information portrayals specifically from information in a progressive layer based structure. Over the last years deep learning processes have been shown to outperform traditional machine learning techniques and procedures in several fields, prominently in computer vision.
Some of the most significant deep learning tools used in computer vision system are convolutional neural networks, deep boltzmann machines and deep belief networks, and stacked de-noising auto-encoders. In January 2016, Movidius, a U.S. based company collaborated with Google Inc. to enhance deep learning capabilities on mobile devices. In September 2016, Intel Corporation announced the acquisition of Movidius for improvising its computer vision and deep learning solutions. All the collaborations and partnerships made by the organizations to make advancements in computer vision technology.

Market Segmentation:

The global deep learning in computer vision market can be segmented in solutions, hardware, application, end user and geographical segments.

• Based on solutions
• Based on hardware
• Based on application
• Based on end user
• Based on geography

Competitive Analysis:

The global deep learning in computer vision market is fragmented and the major players have used various strategies such as new product launches, expansions, agreements, joint ventures, partnerships, acquisitions, and others to increase their footprints in this market in order to sustain in long run. The report includes market shares of deep learning in computer vision market for global, Europe, North America, Asia Pacific and South America.

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