NEURAL NETWORK TECHNOLOGIES IN OBJECT DETECTION AND CLASSIFICATION
S.M. Borzov, E.S. Nezhevenko
Institute of Automation and Electrometry, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia
Keywords: neural network technologies, image processing, object detection and classification, convolutional neural networks, deep learning, combined methods
Abstract
The main ideas used in solving the problems of detecting and classifying objects by their images using neural network technologies are reviewed. The key publications devoted to the most popular ways to improve the accuracy of classification are considered. It is shown that neural network methods of object detection have achieved significant success in the last decade due to the use of convolutional technologies and practical implementation of the idea of deep learning using large visual databases. The main disadvantages, limitations, and possible directions of development of existing approaches are considered and analyzed.
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