COMPARISON OF OBJECT DETECTION BY ARTIFICIAL INTELLIGENCE IN COMPARISON WITH CLASSICAL METHODS

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Vladimir Mikhailovich Zuev
Head of the Department of Intelligent Robotic Systems, Federal State Budget Scientific Institution "Institute of Artificial Intelligence Problems".
283048, 118 b Artyoma str., Donetsk.
Research interests: computer information technologies.

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UDC 528.013
DOI 10.24412/2413-7383-2024-3-30-35
Language: Russian
Annotation: Nowadays, neural networks are increasingly being used to detect objects in a video image. The article presents a comparison of object detection methods using artificial intelligence and classical methods. The use of a neural network is not always justified. Traditional filtering methods often restore the image better at low signal-to-noise ratios, require less memory (which is important when implemented on microprocessors), have greater speed and load the processor less.
Keywords: artificial intelligence, filtering, neural network.

List of literature:
1. TR-MISR: Multiimage Super-Resolution Based on Feature Fusion with Transformers. – Text: electronic // arXiv.org: [website]. – URL: https://ieeexplore.ieee.org/ stamp/ stamp.jsp?arnumber=9684717 (accessed 16.05.2024).
2. Deep Burst Super-Resolution. – Text: electronic // arXiv.org: [website]. –URL: https://arxiv.org/pdf/2101.10997v2 (accessed 16.05.2024).
3. Multi-image Super Resolution of Remotely Sensed Images using Residual Feature Attention Deep Neural Networks. — Text: electronic // arXiv.org: [website]. – URL: https://arxiv.org/ pdf/2007.03107v2 (accessed 16.05.2024).
4. Andreev, A. Yu. Research of multi-frame super-resolution technology for noisy images / A. Yu. Andreev. – Text: direct // Young scientist. – 2024. – No. 20 (519). – URL: https://moluch.ru/archive/519/114343/ (accessed 21.05.2024).
5. M.S. Moseva, K.R. Kharrasov On existing methods of noise removal in images Engineering Bulletin of the Don, No. 8 (2023) ivdon.ru/ru/magazine/archive/n8y2023/8643
6. Medvedeva, E. V. digital image processing in video information systems./ E. V. Medvedeva – Kirov: VyatSU, 2015. – 107 p.
7. V.M. Zuev. Comparison of detection by the classical method. Artificial intelligence: theoretical aspects, practical application: materials of the Donetsk international round table.-Donetsk, FSBSI "IPII" 2023.-252 p.DOI 10.34757/dntsk/AI/2023/30/008
8. Tikhonov V. I. Statistical radio engineering.” 2nd ed., revised and supplemented. M.: Radio and communication, 1962.” 624 p.
9. Anisimov B.V. Kurganov V.D. Zlobin V.K. Recognition and digital image processing. M.«Higher school» 1983 295p.
10. Potapov A.A. and others. The latest methods of image processing. Edited by Potapov A.A. M. FIZMATLIT, 2008.-496 p-ISBN 978-5-9221-0841-6
11. Methods of computer image processing Edited by Soifer V.A. 2nd ed. M. FIZMATLIT, 2003. 784 p. ISBN 5-9221-0270-2
12. Fisenko V.T., Fisenko T.Yu., Computer processing and recognition of images: textbook. - St. Petersburg: St. Petersburg State University ITMO, 2008. – 192 p.
13. Andriyanov NA, Dementiev VE, Tashlinskiy AG. Detection of objects in the images: from likelihood relationships towards scalable and efficient neural networks. Computer Optics 2022; 46(1): 139-159. DOI: 10.18287/2412-6179-CO-922.

Release: 3(34)'2024
Chapter: ROBOTS, MECHATRONICS AND ROBOTIC SYSTEMS
How to quote: Zuev V. M. COMPARISON OF OBJECT DETECTION BY ARTIFICIAL INTELLIGENCE IN COMPARISON WITH CLASSICAL METHODS [Text] / V. M. Zuev // Problems of artificial intelligence. - 2024. № 3 (34). - P. 30-35. - http://paijournal.guiaidn.ru/ru/2024/3(34)-3.html

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