Northbrook, IL 60062 -- (SBWIRE) -- 05/20/2022 -- AI in computer vision is introducing a new level of interaction to the internet. While many find that AI-powered computer vision systems can lead to better customer experiences and product recommendations, others look at the potential complications. Look at this guide for market segments that it could impact.
Computer vision systems are becoming more affordable and accessible, and they are being adopted in a variety of markets. Analysts predict that AI-powered computer vision systems will have a significant impact on the automotive market, healthcare, retail, and manufacturing industries.
The AI in computer vision market is estimated to be valued at USD 15.9 billion in 2021 and reach USD 51.3 billion by 2026, at a CAGR of 26.3%.
The automotive market is forecast to be the largest market for AI-powered computer vision systems in the next five years. The automotive industry is rapidly evolving, and new technologies are being introduced at a rapid pace. Automotive manufacturers are looking for ways to improve safety and efficiency of their vehicles. AI-powered computer vision systems could help them achieve these goals by improving the accuracy of collision detection and diagnostics. Additionally, AI-powered computer vision systems could be used to improve navigation and parking capabilities.
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The healthcare sector is also growing rapidly, and AI-powered computer vision systems could have a significant impact on the way patients are treated. These systems could be used to identify diseases and injuries early in the process, which would allow doctors to make more informed decisions about treatment. Additionally, AI-powered computer vision systems could be used to monitor patients while they are hospitalized or during their clinical trials. This information could be used to improve patient care overall.
AI in Computer Vision Market by Component, Machine Learning Models, Function, Application
Machine learning models are the key component of AI in the computer vision market. They are responsible for extracting knowledge from data and learning on their own. The machine learning models used in AI include deep learning, natural language processing, and neural networks.
Functional areas of AI that are expected to experience the most growth in the coming years include video processing and object recognition. Video processing is essential for tasks such as detecting objects, understanding scenes, and tracking moving objects. Object recognition is used to identify specific objects in images or videos and can be used for tasks such as identifying people, animals, vehicles, and objects in scenes.
Applications of AI in Computer Vision
Computer vision is an essential tool for many businesses and organizations. By automating image recognition, computer vision can save businesses time and money. However, there are many different markets that AI-powered computer vision systems could impact.
1. Retail: Computer vision can help identify products in a warehouse, monitor inventory levels, and optimize storage space.
2. Insurance: Computer vision can analyze images of vehicles to determine if they have been damaged in a crash. This information can be used to generate insurance claims or adjust rates accordingly.
3. Logistics: Computer vision can help drivers locate packages on a truck or identify objects in a warehouse that need to be handled with care.
4. Healthcare: Computer vision can help doctors diagnose medical conditions by analyzing x-rays and scans. This technology is being used increasingly in hospitals around the world.
The AI in computer vision market was dominated by, NVIDIA (US), Microsoft Corp. (US), Intel Corporation (US), IBM Corporation (US) and Qualcomm Technologies, Inc. (US).