The Global Deep Neural Networks Market is projected to reach USD 5.98 billion in 2027. The market is expected to be driven owing to extensive rise in the big data analytics, emergence of the deep learning through neural networks and cognitive analytical procedures in various verticals including IT & Telecommunication, BFSI, e-commerce, and healthcare, among others. The rising implementation of the deep neural networks in clinical diagnosis, image & signal analysis and interpretation, and drug & vaccine development, among others, are propelling the market growth broadly. The BFSI sector segment had a mentionable market share due to numerous application areas related to financial analysis, predictive costing, risk investigation, and others.

The global Deep Neural Networks market report by Emergen and Research is the latest document covering the changes in the market dynamics and trends that have followed the COVID-19 outbreak. The global health emergency has brought about unprecedented changes in the global economic scenario, drastically affecting the Deep Neural Networks market landscape, disrupting its supply chains, and causing volatility in prices and demand for products. The report analyzes the impact of the pandemic on the Deep Neural Networks industry and highlights its beleaguered segments. However, our analysts speculate that the market will regain traction in the post-COVID scenario.

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Competitive Scenario

Google, Oracle, Microsoft, IBM, Qualcomm, Intel, Ward Systems, Starmind, Neurala, NeuralWare, and Clarifai, among others.

Market Report Segmentation

Emergen Research has segmented into the global Deep Neural Networks Market on the basis of Component, Application, Deployment Mode, End-Use Verticals, and region:

Component Outlook (Revenue: USD Billion; 2017-2027)

Software & Application

Services

Application Outlook (Revenue: USD Billion; 2017-2027)

Data Preprocessing

Analytical Tools

Visualization

Optimization

Others

Deployment Mode Outlook (Revenue: USD Billion; 2017-2027)

Cloud

On-Premises

End-Use Verticals Outlook (Revenue: USD Billion; 2017-2027)

BFSI

IT & Telecommunication

Electronics & Semiconductors

Aerospace & Defense

Healthcare & Biotechnology

Energy & Utilities

Manufacturing Industries

Retail & E-Commerce

Others

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Some Key Highlights from the Report

Software and applications are the most commonly used attributes that have been incorporating deep neural networksin use for research simulators, building visualization to monitor training process, simulate the behavior of the consumers using the apps and software, among others. Software and application sub-segment is growing at a CAGR of 22.6% throughout the forecast period.

The market is projected to see a substantial growth owing to its huge implementation in various sectors especially in North American region. Increasing use of advanced technology in BFSI, IT & Telecommunication and Healthcare sectors is anticipated to stimulate demand for the deep neural networks in the region.

The deep neural networks are widely used in the field of visualization and visual analytics for the communicating information and discovering meaningful insights by using various visual encodings to transform the abstract data into useful representations.

In 2018, Switzerland based leading AI Tech company, Starmind, announced an investment of USD 15 Million in its self-learning next generation designing and algorithms, based on the artificial neural network.

Regional Segmentation

North America (U.S., Canada)

Europe (U.K., Italy, Germany, France, Rest of EU)

Asia Pacific (India, Japan, China, South Korea, Australia, Rest of APAC)

Latin America (Chile, Brazil, Argentina, Rest of Latin America)

Middle East & Africa (Saudi Arabia, U.A.E., South Africa, Rest of MEA)

In conclusion, the report provides a qualitative and quantitative analysis of the Global Deep Neural Networks market, including the global and regional analysis of the market. The study covers critical information and factual data about the Deep Neural Networks market industry, along with an in-depth statistical analysis of the market drivers, limitations, growth prospects, opportunities, and threats. On the basis of the current market scope, the report provides an extensive analysis of how the Deep Neural Networks market is expected to fare in the forecast timeline. The report utilizes Deep Neural Networks analytical tools to offer an estimation of the outlook of the global state of the Deep Neural Networks market industry.

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