Global Deep Neural Networks Market Forecast to 2027
The Global Deep Neural Networks Market research report is a complete study that summarizes the most recent changes and advancements in the Deep Neural Networks industry, with 2018 acting as the base year and the forecast year being 2020–2027. The analysis provides useful details on the market's size, share, sales channels, distribution system, market segmentation, consumer needs, industry trends, and potential for future growth. The research also looks at both global and regional market growth. The paper examines the COVID-19 pandemic's implications for the market for Deep Neural Networks and its key segments.
The Global Deep Neural network Market is projected to reach USD 5.98 billion in 2027. The market is expected to be driven by the extensive rise in big data analytics, the emergence of deep learning through neural networks, and cognitive analytical procedures in various verticals, including IT and telecommunications, BFSI, e-commerce, and healthcare, among others. The rising implementation of deep neural networks in clinical diagnosis, image and signal analysis and interpretation, and drug and vaccine development, among others, is propelling 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.
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Competitive Terrain:
The global Deep Neural Networks industry is highly consolidated owing to the presence of renowned companies operating across several international and local segments of the market. These players dominate the industry in terms of their strong geographical reach and a large number of production facilities. The companies are intensely competitive against one another and excel in their individual technological capabilities, as well as product development, innovation, and product pricing strategies.
The leading market contenders listed in the report are:
Google, Oracle, Microsoft, IBM, Qualcomm, Intel, Ward Systems, Starmind, Neurala, NeuralWare, and Clarifai
Research Report on the Deep Neural Networks Market Addresses the Following Key Questions:
- Who are the dominant players of the Deep Neural Networks market?
- Which regional market is anticipated to have a high growth rate over the projected period?
- What consumer trends and demands are expected to influence the operations of the market players in the Deep Neural Networks market?
- What are the key growth drivers and restraining factors of the Deep Neural Networks market?
- What are the expansion plans and strategic investment plans undertaken by the players to gain a robust footing in the market?
- What is the overall impact of the COVID-19 pandemic on the Deep Neural Networks market and its key segments?
Market Overview:
The report bifurcates the Deep Neural Networks market on the basis of different product types, applications, end-user industries, and key regions of the world where the market has already established its presence. The report accurately offers insights into the supply-demand ratio and production and consumption volume of each segment.
Segments Covered in this report are:
- 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
Regional Landscape section of the Deep Neural Networks report offers deeper insights into the regulatory framework, current and emerging market trends, production and consumption patterns, supply and demand dynamics, import/export, and presence of major players in each region.
The various regions analyzed in the report include:
- 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)
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Further key findings from the report suggest
- Software and applications are the most commonly used attributes that have been incorporating deep neural networks in 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.
The section on the competitive landscape offers valuable and actionable insights related to the business sphere of the Deep Neural Networks market, covering extensive profiling of the key market players. The report offers information about market share, product portfolio, pricing analysis, and strategic alliances such as mergers and acquisitions, joint ventures, collaborations, partnerships, product launches and brand promotions, among others. The report also discusses the initiatives taken by the key companies to combat the impact of the COVID-19 pandemic.
Key Points of the Geographical Analysis:
- Data and information related to the consumption rate in each region
- Estimated increase in the consumption rate
- Proposed growth of the market share of each region
- Geographical contribution to market revenue
- Expected growth rate of the regional markets
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