Computer vision technology is very popular in retail industry. After finding the goods they want, shoppers can leave without scanning the goods or paying. AI will detect what items shoppers have taken away, and the system will automatically charge their account. Computer vision is to use computer to simulate human eyes to recognize, track and measure targets, and to recognize, interpret and process graphics and images, that is, to realize computer "understanding". It has become one of the key technologies that AI has taken the lead in making great breakthroughs and clear application scenarios. With the continuous progress of deep learning technology, the expansion of computing storage and the surge of visual data, computer vision has flourished in recent years. In fact, in less than a decade, the accuracy of computer vision technology has increased from 50% to 99%, and its business application field and market scale are also increasing day by day. In 2020, the global market scale of computer vision was US $9.45 billion, and it is expected to reach US $41.11 billion by 2030. In the recent report of Forbes biweekly, the United States listed the five industries that are most likely to "show their talents" in this technology. medical care In recent years, the medical care industry is increasingly using computer vision technology to improve patient prognosis and improve efficiency. One of the main applications of computer vision in medical care is to analyze scanned images, which can not only detect personal abnormalities, but also recognize the patterns of thousands of scans, so as to provide doctors with information about a certain disease. Computer vision can usually notice patterns that human eyes cannot recognize. For example, subtle differences in the appearance of some cancer cells can only be detected by computer vision and artificial intelligence analysis. A study on breast cancer screening showed that the visual artificial intelligence system showed higher accuracy than human radiologists in finding signs of breast cancer in breast X-rays, thereby reducing the number of false positives and false negatives and reducing human workload by 88%. For example, last year, Britain and the European Union approved the breast cancer diagnosis technology called panprofiler for clinical use in health service institutions. It can provide the diagnostic reading of the initial image within 15 minutes, and its accuracy is comparable to the laboratory detection method that takes several weeks to complete, providing a faster and cheaper alternative than traditional detection. Computer vision is also used to prevent accidents in hospitals. For example, a camera driven by computer vision can detect the time when doctors forget to disinfect tools or leave foreign bodies in patients during surgery, and then notify them of an error. retail Computer vision is also "expanding" in the retail industry. For example, retailers can create heat maps and analyze customer action tracks, so as to have an in-depth understanding of customers' behavior in the store, so as to try different marketing strategies to increase sales. For example, Amazon, a famous retailer, is using advanced computer vision technology to allow shoppers to leave without scanning or paying after finding the goods they want. AI will detect what items shoppers have taken away, and the system will charge their Amazon account. Computer vision can also significantly improve the efficiency of inventory management, because this technology can identify the items in images or videos and the number of crates, without manual inventory by workers. These automated inventory cycle counts provide retail workers with real-time updates that enable them to make informed decisions about inventory levels. It is reported that 64% of retailers plan to deploy data-driven solutions such as computer vision in the next few years to optimize inventory management. Automobile industry Computer vision can also be widely used in the automotive industry. For example, in the production process, it can detect the defects of products, which helps to ensure that products meet quality standards. The camera placed on the production line can detect these defects and remind the manufacturing workers in real time. In fact, in a study, computer vision algorithm can detect the fault of brake parts with an accuracy of 95.6%. In addition, computer vision is also an indispensable part of today's autonomous vehicle. This technology can be used to identify objects on the road, create 3D maps, detect lane lines, and help drivers drive in dim light. Tesla, an electric vehicle manufacturer, announced in 2021 that its new car would rely entirely on computer vision rather than lidar. The company's chief AI scientist said that the deep learning system was "100 times better than radar". catering The catering industry is one of the industries hardest hit by the COVID-19, and many enterprises are forced to digitalize and innovate to survive. More and more restaurant chains are adopting AI innovations to help them improve efficiency and minimize costs. Computer vision technology enables restaurants to reduce customers' long waiting times, optimize the use of their floor space, and even monitor whether customers wear masks in compliance. For example, a start-up company is using computer vision technology to help fast food restaurants minimize wrong orders and improve operational efficiency. At the same time, another startup is using computer vision to help restaurants speed up processes and evaluate customer experience. Companies use this technology to measure how long customers wait in restaurants and to upgrade their security systems. Energy and utilities In the energy and utility industries, computer vision is improving operational efficiency, improving safety, and helping prevent accidents. For example, the staff can use computer vision to analyze the image of the electric pole, so as to detect the defects that may cause fire in the electric pole. Based on this, the utility company can decide whether to pay attention to these abnormalities immediately and prevent the occurrence of extreme events. In addition to detecting anomalies, the application of computer vision in the energy and utility industries also includes ensuring the safety of the workplace. For example, the deep learning algorithm can analyze the video in real time and remind employees to pay attention to the danger, and find the behavior of violating the security agreement or invading the work area. Forbes biweekly pointed out in the report that computer vision technology is expected to be further adopted in the next few years because it can help improve efficiency, save time and resources, improve accuracy and security. (Xinhua News Agency)