DMP Soft
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Computer vision
Computer vision is the process of recognizing objects and features in digital images or video. It is a key area of technology that enables us to interact with digital content in ways that were not possible before. Computer vision[1] is a subfield of artificial intelligence, and is the ability of computers to recognize objects, actions, scenes, etc. in images or videos.
how it work ? it enables user to locate and identify objects in an image, such as people, cars, animals, etc... The accuracy depends on several factors: image resolution, illumination, presence of background clutters (for example road signs), background patterns and their complexity, and object's size and pose.
In 2012, Google announced the development of "Google Vision",[2] a set of computer vision algorithms that enables users to upload an image and obtain text recognition results and additional image information. The project's code is open source and it is distributed as a computer program on GitHub.
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Convolutional neural networks were developed by Alex Krizhevsky and Ilya Sutskever for visual recognition and natural language processing in 2012.
Computer vision is a subfield of artificial intelligence,[3] and is the ability of computers to recognize objects, actions, scenes, etc. in images or videos. It is also the study of the techniques and methodologies behind this process. Computer vision usually refers to the analysis of still images, but it can also apply to other types of media such as video. It can also be considered a subset of machine vision.
The term "computer vision"[4] is sometimes used to refer to a broader set of technologies, including machine vision, computer vision, image processing, pattern recognition, and machine learning. It is the application of computer technology to the field of image analysis.
Some of the computer-vision techniques include motion analysis, pattern recognition, learning by example, and the use of machine learning for data analysis and inference. Computer vision[5] is also applied to the problem of computer vision, in particular for three-dimensional computer vision.
conclusion : This technologie will very probably be used to improve solutions for real problems in professional fields such as self-driving cars or helping doctors to perform surgery without performing too many errors and save human lives. Computer Vision is a subfield of computer science that deals with how computers perceive their environments and[6] how to extract information from images or videos. Some commonly used applications include face detection, object detection, image classification and image tracking. A deeper understanding of these techniques can improve the capabilities of many technological devices. Computers today have complex and sophisticated systems for recognizing faces and performing tasks like interpreting voice commands and understanding images. However, computer vision[7] (and more specifically face detection) is still an active area of research, and new techniques are constantly being developed as technology advances. Computer vision systems are increasingly being used in business, industry, medicine, and other areas.
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