Market Overview:
The global deep learning software market is expected to grow at a CAGR of 31.5% during the forecast period from 2018 to 2030. The growth of the market can be attributed to the increasing demand for artificial intelligence (AI) and machine learning across industries, rising adoption of cloud-based services, and growing demand for deep learning software in SMEs. Based on type, the global deep learning software market is segmented into artificial neural network software, image recognition software, and voice recognition software.
Product Definition:
Deep learning software is a type of artificial intelligence software that uses neural networks to learn how to recognize patterns. It is important because it can be used to identify objects or patterns in data that are too difficult for humans to discern. This makes it useful for tasks such as image recognition, speech recognition, and natural language processing.
Artificial Neural Network Software:
Artificial neural network (ANN) is a learning technology that enables computers to learn from experience by imitation of biological neural networks. ANN provides flexibility to tackle new problems by allowing the construction of different types of networks, with varying numbers of nodes and connections. Artificial neural network software is used for training artificial intelligence systems or deep learning systems which are then applied in various industry verticals such as healthcare, finance, retail etc.
Image Recognition Software:
The image recognition software is used to identify objects and events in the images. It extracts information from the images by using pattern recognition techniques. The patterns that are recognized can be used for various applications such as search engines, optical character recognition, video surveillance, and face identification among others. Image Recognition Software is an important aspect of deep learning software as it helps in training neural networks for various tasks such as object detection, categorization or identification of a person etc.
Application Insights:
The large enterprises segment dominated the global deep learning software market in 2017. The segment is expected to maintain its dominance over the forecast period owing to factors such as extensive R&D capabilities of large enterprises and high adoption of advanced AI techniques by these companies. For instance, in October 2017, Microsoft launched a new version of its Office application for Mac with built-in support for machine learning algorithms that enable users to create more effective documents using less effort.
The SMEs or small and medium-sized businesses segment is expected to register the highest CAGR over the forecast period due largely to increasing penetration of deep learning technologies among these companies which are yet not big enough or have sufficient resources required for research & development activities related AI applications.
Regional Analysis:
North America dominated the market in 2017. The growth can be attributed to increased funding for deep learning research, growing adoption of Deep Learning based services and products by key players such as IBM Corporation; Google LLC; Microsoft Corporation; and Amazon Web Services, Inc. Europe is expected to witness significant growth over the forecast period owing to increasing investments in artificial intelligence-related technologies by governments across countries such as U.K., Germany, France, Italy among others. Moreover, rising demand for voice-enabled applications is anticipated to drive regional market growth during the forecast period.
Asia Pacific region is projected to exhibit a high CAGR over the forecast period owing with rapid advancements in technology coupled with increasing government initiatives aimed at promoting digitalization across various economies including China.
Growth Factors:
- Increasing demand for Deep Learning software from various industry verticals
- Growing number of start-ups and venture capitalists investing in Deep Learning technology
- Rising popularity of open source platforms and tools for Deep Learning development
- Proliferation of big data and the increasing need for advanced analytics solutions
- Emergence of artificial intelligence as a key application area for Deep Learning
Scope Of The Report
Report Attributes
Report Details
Report Title
Deep Learning Software Market Research Report
By Type
Artificial Neural Network Software, Image Recognition Software, Voice Recognition Software
By Application
Large Enterprises, SMEs
By Companies
Microsoft, Express Scribe, Nuance, Google, IBM, AWS, AV Voice, Sayint, OpenCV, SimpleCV, Clarifai, Keras, Mocha, TFLearn, Torch, DeepPy
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
191
Number of Tables & Figures
134
Customization Available
Yes, the report can be customized as per your need.
Global Deep Learning Software Market Report Segments:
The global Deep Learning Software market is segmented on the basis of:
Types
Artificial Neural Network Software, Image Recognition Software, Voice Recognition Software
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Large Enterprises, SMEs
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- Microsoft
- Express Scribe
- Nuance
- Google
- IBM
- AWS
- AV Voice
- Sayint
- OpenCV
- SimpleCV
- Clarifai
- Keras
- Mocha
- TFLearn
- Torch
- DeepPy
Highlights of The Deep Learning Software Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- Artificial Neural Network Software
- Image Recognition Software
- Voice Recognition Software
- By Application:
- Large Enterprises
- SMEs
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Deep Learning Software Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
How you may use our products:
- Correctly Positioning New Products
- Market Entry Strategies
- Business Expansion Strategies
- Consumer Insights
- Understanding Competition Scenario
- Product & Brand Management
- Channel & Customer Management
- Identifying Appropriate Advertising Appeals
8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Deep learning software is a type of software that helps computers learn how to do tasks by themselves. Deep learning algorithms are used to create these programs, which can then be used to recognize patterns in data or perform other tasks.
Some of the key players operating in the deep learning software market are Microsoft, Express Scribe, Nuance, Google, IBM, AWS, AV Voice, Sayint, OpenCV, SimpleCV, Clarifai, Keras, Mocha, TFLearn, Torch, DeepPy.
The deep learning software market is expected to grow at a compound annual growth rate of 31.5%.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Deep Learning Software Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Deep Learning Software Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Deep Learning Software Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Deep Learning Software Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Deep Learning Software Market Size & Forecast, 2018-2028
4.5.1 Deep Learning Software Market Size and Y-o-Y Growth
4.5.2 Deep Learning Software Market Absolute $ Opportunity
Chapter 5 Global Deep Learning Software Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Deep Learning Software Market Size Forecast by Type
5.2.1 Artificial Neural Network Software
5.2.2 Image Recognition Software
5.2.3 Voice Recognition Software
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Deep Learning Software Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Deep Learning Software Market Size Forecast by Applications
6.2.1 Large Enterprises
6.2.2 SMEs
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Deep Learning Software Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Deep Learning Software Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Deep Learning Software Analysis and Forecast
9.1 Introduction
9.2 North America Deep Learning Software Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Deep Learning Software Market Size Forecast by Type
9.6.1 Artificial Neural Network Software
9.6.2 Image Recognition Software
9.6.3 Voice Recognition Software
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Deep Learning Software Market Size Forecast by Applications
9.10.1 Large Enterprises
9.10.2 SMEs
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Deep Learning Software Analysis and Forecast
10.1 Introduction
10.2 Europe Deep Learning Software Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Deep Learning Software Market Size Forecast by Type
10.6.1 Artificial Neural Network Software
10.6.2 Image Recognition Software
10.6.3 Voice Recognition Software
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Deep Learning Software Market Size Forecast by Applications
10.10.1 Large Enterprises
10.10.2 SMEs
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Deep Learning Software Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Deep Learning Software Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Deep Learning Software Market Size Forecast by Type
11.6.1 Artificial Neural Network Software
11.6.2 Image Recognition Software
11.6.3 Voice Recognition Software
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Deep Learning Software Market Size Forecast by Applications
11.10.1 Large Enterprises
11.10.2 SMEs
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Deep Learning Software Analysis and Forecast
12.1 Introduction
12.2 Latin America Deep Learning Software Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Deep Learning Software Market Size Forecast by Type
12.6.1 Artificial Neural Network Software
12.6.2 Image Recognition Software
12.6.3 Voice Recognition Software
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Deep Learning Software Market Size Forecast by Applications
12.10.1 Large Enterprises
12.10.2 SMEs
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Deep Learning Software Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Deep Learning Software Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Deep Learning Software Market Size Forecast by Type
13.6.1 Artificial Neural Network Software
13.6.2 Image Recognition Software
13.6.3 Voice Recognition Software
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Deep Learning Software Market Size Forecast by Applications
13.10.1 Large Enterprises
13.10.2 SMEs
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Deep Learning Software Market: Competitive Dashboard
14.2 Global Deep Learning Software Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 Microsoft
14.3.2 Express Scribe
14.3.3 Nuance
14.3.4 Google
14.3.5 IBM
14.3.6 AWS
14.3.7 AV Voice
14.3.8 Sayint
14.3.9 OpenCV
14.3.10 SimpleCV
14.3.11 Clarifai
14.3.12 Keras
14.3.13 Mocha
14.3.14 TFLearn
14.3.15 Torch
14.3.16 DeepPy
