Training Function to Grow at a Higher CAGR in AI in Computer Vision Market, Projected to Reach $51.3 Billion by 2026
By 2026, it is anticipated that the AI in Computer Vision Market would be worth USD 51.3 billion. The rise in demand for computer vision systems in novel and developing applications, such as quality control and automation, is credited with driving the market expansion. Government measures to assist industrial automation and the integration of artificial intelligence (AI) into edge devices, as well as the demand for application-specific integrated circuits (ASICs), are additional factors predicted to fuel market expansion. However, the market for AI in Computer Vision may be constrained by the escalating security issues around cloud-based image processing and analytics.
The hardware and software that make up computer vision applications are divided into different market segments. From 2021 to 2026, the CAGR for the software segment is anticipated to be higher, indicating faster growth. Individuals can interact with a camera and manufacturing line using the software tools and a variety of computer vision applications to do tasks including picture improvement, flaw identification, position analysis, character verification, character recognition, and symbol recognition, among others. The AI in computer vision market is divided into two functional categories: training and inference, with the inference function predicted to occupy a greater market share by 2026. Inference functions' expanding use in picture and object recognition, object detection, and image segmentation is anticipated to fuel this market's expansion in the years to come.
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The market for AI in computer vision is propelled by the rise in automation and quality control requirements across numerous sectors. Regions, verticals, components, and functionalities are used to segment the market. Due to the sensitivity to latency and the requirement for the infrastructure to accelerate the data at the fastest rate, the inference function segment is anticipated to have a greater proportion of the market by 2026. Due to the computational cost of creating algorithms that may infer a result from data or processes, the training function sector is anticipated to increase at a higher CAGR over the projected period. Machine learning models are the foundation of the AI in computer vision industry, with supervised learning predicted to hold the greatest market share by 2026, accounting for approximately 84% of the whole market.
Industrial and non-industrial applications make up the two market segments for AI in computer vision. Since current technology may assist in numerous traffic scenario systems, such as toll collection, monitoring traffic flows, and recognising violations, the industrial section is anticipated to grow more quickly.
In non-industrial applications like security and surveillance, postal and logistics, and intelligent transportation systems (ITS), where picture quality, dimension, and orientation are critical, 3D machine vision also has a significant growth potential. Many transportation systems, including toll collecting and traffic monitoring systems, can be improved by contemporary technologies.
The market for AI in computer vision, particularly in the consumer sector, is being driven by the rising demand for smartphones with cameras on the front and back ends. Higher pixel counts are being driven by rear-end cameras, while front-end cameras have a lower pixel count and rely on fixed-focus technology.
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According to the end-use industry, the AI in computer vision market has been divided into a number of sectors. Between 2021 and 2026, the healthcare sector is expected to see a considerable CAGR. A wide range of solutions are offered by AI in computer vision, including predictive analytics, virtual nursing assistants, medical imaging & diagnostics, and drug development. The adoption of AI-based medical imaging and diagnostics has also been accelerated by the COVID-19 epidemic, fueling the expansion of the healthcare industry.
The increased use of AI-based computer vision technologies for tracking consumer behaviour, demand forecasting, and supply chain optimization is another factor contributing to the retail sector's predicted faster growth. AI in computer vision is being used in the agriculture industry for weed detection, yield calculation, and crop monitoring. The demand for AI-based computer vision systems for automated inspection, predictive maintenance, and route optimization is also rising in the transportation and logistics sector.
The AI in computer vision market is predicted to expand at the greatest CAGR in the APAC region. The main market contributors in APAC are anticipated to be China, Japan, and South Korea. In China, increased manufacturing operations are the main driver of economic growth, whereas India is seeing an enormous increase in demand for Industry 4.0 and advanced manufacturing techniques to increase automation across a variety of applications, which is fueling the tremendous growth of AI in computer vision in APAC. Additionally, it is anticipated that the market for AI in computer vision in this area would develop as a result of nations like Singapore and China investing more in R&D initiatives connected to AI and machine learning technologies. The market in APAC is expanding as a result of the rising demand for automation and robotics solutions in a number of industries, including agriculture, healthcare, and the automotive industries.
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