Market Overview:
The global deep learning in machine vision market is expected to grow at a CAGR of 27.5% during the forecast period from 2018 to 2030. The growth of the market can be attributed to the increasing demand for deep learning in machine vision across different applications such as automotive, electronic, food and drink, health care, aerospace and defense, and others. Additionally, factors such as rising adoption of artificial intelligence (AI) and growing demand for smart factories are also contributing to the growth of the global deep learning in machine vision market.
Product Definition:
Deep learning is a subset of machine learning, which is a field of artificial intelligence. It refers to algorithms that can learn to recognize patterns in data, without being explicitly programmed to do so. Deep learning networks are composed of many layers, or neurons, that can learn how to identify different features in an image or other type of data.
Hardware:
Hardware is the part of technology that helps to create, modify or destroy the form of digital information. In deep learning in machine vision market hardware means all electronic devices and components which are used to capture, process and store data. It can be further segmented into input devices such as cameras, scanners, keypads etc., output device & display screens etc., storage mediums such as hard drives memory cards etc., processing unit (CPU)s and output devices (monitor).
Software:
Software is the collection of tools and techniques that are used to create, modify, analyze or optimize computer software. In other words, it is a set of procedures that allow the execution of programs and facilitate data processing on personal computers, workstations or servers. Software can be seen as an electronic document which allows users to perform specified tasks with the help of input parameters.
The global deep learning in machine vision market size was valued at USD 859.6 million in 2016.
Application Insights:
The application segment is segregated into automobile, electronics, food and drink, health care, aerospace and defense. The automobile application segment accounted for the largest market share in 2017 owing to the high adoption of deep learning algorithms in image recognition systems for vehicle safety. Moreover, increasing demand for autonomous vehicles is expected to drive this industry over the forecast period.
The electronic segment is anticipated to register a significant CAGR over the forecast period due to growing usage of deep learning algorithms in smart devices such as televisions and set-top boxes (STB). Furthermore, these technologies are also used extensively across several other applications such as vision-based security solutions within internet-of-things (IoT) devices.
Deep learning has numerous applications across various industries including healthcare & pharmaceuticals where it helps automate processes such as drug discovery and testing by identifying patterns from large datasets with neural networks.
Regional Analysis:
The market in North America is expected to grow at a significant rate over the forecast period owing to increasing investments by companies in the region. For instance, In January 2017, Google Inc. announced an investment of USD X million for DeepMind Technologies Ltd., a London-based artificial intelligence company that has developed learning algorithms based on artificial neural networks and deep learning for computer vision applications. The algorithm powers Google Photos app to detect objects in photos and suggests tags for users. Such investments are anticipated to drive regional growth over the forecast period.
Asia Pacific is estimated to be one of the fastest growing regions due high adoption of these technologies across various industrial sectors such as manufacturing, automotive, healthcare & life sciences.
Growth Factors:
- Increasing demand for Deep Learning in Machine Vision from the automotive industry for advanced driver assistance systems (ADAS) and autonomous driving.
- Growing demand for Deep Learning in Machine Vision from the retail sector for automated checkout and inventory management.
- Increasing use of Deep Learning in Machine Vision by medical device manufacturers to improve accuracy of image-based diagnostics.
- Proliferation of low-cost, deep learning-enabled edge devices that can be used to deploy machine vision applications at the network edge.
Scope Of The Report
Report Attributes
Report Details
Report Title
Deep Learning in Machine Vision Market Research Report
By Type
Hardware, Software
By Application
Automobile, Electronic, Food and Drink, Health Care, Aerospace and Defense, Others
By Companies
IFLYTEK, NavInfo, NVIDIA, Qualcomm, Intel, Beijing Megvii, 4Paradigm
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
184
Number of Tables & Figures
129
Customization Available
Yes, the report can be customized as per your need.
Global Deep Learning in Machine Vision Market Report Segments:
The global Deep Learning in Machine Vision market is segmented on the basis of:
Types
Hardware, 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
Automobile, Electronic, Food and Drink, Health Care, Aerospace and Defense, Others
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:
- IFLYTEK
- NavInfo
- NVIDIA
- Qualcomm
- Intel
- Beijing Megvii
- 4Paradigm
Highlights of The Deep Learning in Machine Vision 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:
- Hardware
- Software
- By Application:
- Automobile
- Electronic
- Food and Drink
- Health Care
- Aerospace and Defense
- Others
- 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 in Machine Vision 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 is a subset of machine learning that uses deep neural networks. These networks are composed of many layers, or neurons, and can learn complex patterns very quickly.
Some of the key players operating in the deep learning in machine vision market are IFLYTEK, NavInfo, NVIDIA, Qualcomm, Intel, Beijing Megvii, 4Paradigm.
The deep learning in machine vision market is expected to register a CAGR of 27.5%.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Deep Learning in Machine Vision 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 in Machine Vision Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Deep Learning in Machine Vision 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 in Machine Vision 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 in Machine Vision Market Size & Forecast, 2020-2028
4.5.1 Deep Learning in Machine Vision Market Size and Y-o-Y Growth
4.5.2 Deep Learning in Machine Vision Market Absolute $ Opportunity
Chapter 5 Global 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 Market Size Forecast by Type
5.2.1 Hardware
5.2.2 Software
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global 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 Market Size Forecast by Applications
6.2.1 Automobile
6.2.2 Electronic
6.2.3 Food and Drink
6.2.4 Health Care
6.2.5 Aerospace and Defense
6.2.6 Others
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Deep Learning in Machine Vision 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 in Machine Vision 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 Analysis and Forecast
9.1 Introduction
9.2 North America 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 Market Size Forecast by Type
9.6.1 Hardware
9.6.2 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 Market Size Forecast by Applications
9.10.1 Automobile
9.10.2 Electronic
9.10.3 Food and Drink
9.10.4 Health Care
9.10.5 Aerospace and Defense
9.10.6 Others
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 Analysis and Forecast
10.1 Introduction
10.2 Europe 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 Market Size Forecast by Type
10.6.1 Hardware
10.6.2 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 Market Size Forecast by Applications
10.10.1 Automobile
10.10.2 Electronic
10.10.3 Food and Drink
10.10.4 Health Care
10.10.5 Aerospace and Defense
10.10.6 Others
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 Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific 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 Market Size Forecast by Type
11.6.1 Hardware
11.6.2 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 Market Size Forecast by Applications
11.10.1 Automobile
11.10.2 Electronic
11.10.3 Food and Drink
11.10.4 Health Care
11.10.5 Aerospace and Defense
11.10.6 Others
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 Analysis and Forecast
12.1 Introduction
12.2 Latin America 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 Market Size Forecast by Type
12.6.1 Hardware
12.6.2 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 Market Size Forecast by Applications
12.10.1 Automobile
12.10.2 Electronic
12.10.3 Food and Drink
12.10.4 Health Care
12.10.5 Aerospace and Defense
12.10.6 Others
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) Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) 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) Market Size Forecast by Type
13.6.1 Hardware
13.6.2 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) Market Size Forecast by Applications
13.10.1 Automobile
13.10.2 Electronic
13.10.3 Food and Drink
13.10.4 Health Care
13.10.5 Aerospace and Defense
13.10.6 Others
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 in Machine Vision Market: Competitive Dashboard
14.2 Global Deep Learning in Machine Vision Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 IFLYTEK
14.3.2 NavInfo
14.3.3 NVIDIA
14.3.4 Qualcomm
14.3.5 Intel
14.3.6 Beijing Megvii
14.3.7 4Paradigm
