The monograph is devoted to the development of computer vision methods and tools using AI for fast identification of moving objects in a video data stream based on deep learning technologies. Classical and non-classical methods of artificial intelligence, convolutional neural networks, computer vision and image recognition, and theories of control systems based on estimates and criteria of mathematical statistics are considered. As a result of recognition, the type of recognised object is determined, and quantitative accuracy estimates are calculated. A method of applying templates is implemented. The algorithm has information about what the sought object looks like, what background it may have, what specific contours of the object look like and in what position they are. The possible location of the object detection is immediately taken into account. It allows for the achievement of high recognition quality and good performance. When a video camera shoots several similar objects, different templates are satisfied, and recognition decreases. Artificial neural network models are used to estimate or approximate functions that may depend on many inputs and are usually unknown.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The monograph is devoted to the development of computer vision methods and tools using AI for fast identification of moving objects in a video data stream based on deep learning technologies. Classical and non-classical methods of artificial intelligence, convolutional neural networks, computer vision and image recognition, and theories of control systems based on estimates and criteria of mathematical statistics are considered. As a result of recognition, the type of recognised object is determined, and quantitative accuracy estimates are calculated. A method of applying templates is implemented. The algorithm has information about what the sought object looks like, what background it may have, what specific contours of the object look like and in what position they are. The possible location of the object detection is immediately taken into account. It allows for the achievement of high recognition quality and good performance. When a video camera shoots several similar objects, different templates are satisfied, and recognition decreases. Artificial neural network models are used to estimate or approximate functions that may depend on many inputs and are usually unknown. 396 pp. Englisch. N° de réf. du vendeur 9786204983189
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Paperback. Etat : new. Paperback. The monograph is devoted to the development of computer vision methods and tools using AI for fast identification of moving objects in a video data stream based on deep learning technologies. Classical and non-classical methods of artificial intelligence, convolutional neural networks, computer vision and image recognition, and theories of control systems based on estimates and criteria of mathematical statistics are considered. As a result of recognition, the type of recognised object is determined, and quantitative accuracy estimates are calculated. A method of applying templates is implemented. The algorithm has information about what the sought object looks like, what background it may have, what specific contours of the object look like and in what position they are. The possible location of the object detection is immediately taken into account. It allows for the achievement of high recognition quality and good performance. When a video camera shoots several similar objects, different templates are satisfied, and recognition decreases. Artificial neural network models are used to estimate or approximate functions that may depend on many inputs and are usually unknown. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9786204983189
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Taschenbuch. Etat : Neu. Computer vision based on machine learning technology: monograph | Information technology for computer vision based on neural networks, artificial intelligence, video/image recognition | Victoria Vysotska (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786204983189 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 131153920
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The monograph is devoted to the development of computer vision methods and tools using AI for fast identification of moving objects in a video data stream based on deep learning technologies. Classical and non-classical methods of artificial intelligence, convolutional neural networks, computer vision and image recognition, and theories of control systems based on estimates and criteria of mathematical statistics are considered. As a result of recognition, the type of recognised object is determined, and quantitative accuracy estimates are calculated. A method of applying templates is implemented. The algorithm has information about what the sought object looks like, what background it may have, what specific contours of the object look like and in what position they are. The possible location of the object detection is immediately taken into account. It allows for the achievement of high recognition quality and good performance. When a video camera shoots several similar objects, different templates are satisfied, and recognition decreases. Artificial neural network models are used to estimate or approximate functions that may depend on many inputs and are usually unknown.Books on Demand GmbH, Überseering 33, 22297 Hamburg 396 pp. Englisch. N° de réf. du vendeur 9786204983189
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The monograph is devoted to the development of computer vision methods and tools using AI for fast identification of moving objects in a video data stream based on deep learning technologies. Classical and non-classical methods of artificial intelligence, convolutional neural networks, computer vision and image recognition, and theories of control systems based on estimates and criteria of mathematical statistics are considered. As a result of recognition, the type of recognised object is determined, and quantitative accuracy estimates are calculated. A method of applying templates is implemented. The algorithm has information about what the sought object looks like, what background it may have, what specific contours of the object look like and in what position they are. The possible location of the object detection is immediately taken into account. It allows for the achievement of high recognition quality and good performance. When a video camera shoots several similar objects, different templates are satisfied, and recognition decreases. Artificial neural network models are used to estimate or approximate functions that may depend on many inputs and are usually unknown. N° de réf. du vendeur 9786204983189
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