Neural network recognition system for video transmitted through a binary symmetric channel
The demand for transmitting video data is increasing annually, necessitating the use of high-quality equipment for reception and processing. The paper presents a neural network recognition system for videos transmitted via a binary symmetrical channel. The presence of digital noise in the data makes...
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| Format: | Article |
| Language: | English |
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Samara National Research University
2024-08-01
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| Series: | Компьютерная оптика |
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| Online Access: | https://www.computeroptics.ru/eng/KO/Annot/KO48-4/480413e.html |
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| author | V.A. Baboshina A.R. Orazaev P.A. Lyakhov E.E. Boyarskaya |
| author_facet | V.A. Baboshina A.R. Orazaev P.A. Lyakhov E.E. Boyarskaya |
| author_sort | V.A. Baboshina |
| collection | DOAJ |
| description | The demand for transmitting video data is increasing annually, necessitating the use of high-quality equipment for reception and processing. The paper presents a neural network recognition system for videos transmitted via a binary symmetrical channel. The presence of digital noise in the data makes it challenging to recognize objects in videos even with advanced neural networks. The proposed system consists of a noise interference detector, a noise purification system based on an adaptive median filter, and a neural network for recognition. The experiment results demonstrate that the proposed system effectively reduces video noise and accurately identifies multiple objects. This versatility makes the system applicable in various fields such as medicine, life safety, physics, and chemistry. The direction of further research may be to improve the model neural network, increasing the database for training or using other noises for modeling. |
| format | Article |
| id | doaj-art-a18b7d01d1314e8d9b4b79a1fc05a25f |
| institution | OA Journals |
| issn | 0134-2452 2412-6179 |
| language | English |
| publishDate | 2024-08-01 |
| publisher | Samara National Research University |
| record_format | Article |
| series | Компьютерная оптика |
| spelling | doaj-art-a18b7d01d1314e8d9b4b79a1fc05a25f2025-08-20T02:12:23ZengSamara National Research UniversityКомпьютерная оптика0134-24522412-61792024-08-0148458259110.18287/2412-6179-CO-1388Neural network recognition system for video transmitted through a binary symmetric channelV.A. Baboshina0A.R. Orazaev1P.A. Lyakhov2E.E. Boyarskaya3North-Caucasus Center for Mathematical Research, North-Caucasus Federal UniversityNorth-Caucasus Center for Mathematical Research, North-Caucasus Federal UniversityNorth-Caucasus Center for Mathematical Research, North-Caucasus Federal University; Department of Mathematical Modeling, North-Caucasus Federal UniversityDepartment of Mathematical Modeling, North-Caucasus Federal UniversityThe demand for transmitting video data is increasing annually, necessitating the use of high-quality equipment for reception and processing. The paper presents a neural network recognition system for videos transmitted via a binary symmetrical channel. The presence of digital noise in the data makes it challenging to recognize objects in videos even with advanced neural networks. The proposed system consists of a noise interference detector, a noise purification system based on an adaptive median filter, and a neural network for recognition. The experiment results demonstrate that the proposed system effectively reduces video noise and accurately identifies multiple objects. This versatility makes the system applicable in various fields such as medicine, life safety, physics, and chemistry. The direction of further research may be to improve the model neural network, increasing the database for training or using other noises for modeling.https://www.computeroptics.ru/eng/KO/Annot/KO48-4/480413e.htmlneural networksvideo recognitionyolobinary symmetric channelvideo denoise |
| spellingShingle | V.A. Baboshina A.R. Orazaev P.A. Lyakhov E.E. Boyarskaya Neural network recognition system for video transmitted through a binary symmetric channel Компьютерная оптика neural networks video recognition yolo binary symmetric channel video denoise |
| title | Neural network recognition system for video transmitted through a binary symmetric channel |
| title_full | Neural network recognition system for video transmitted through a binary symmetric channel |
| title_fullStr | Neural network recognition system for video transmitted through a binary symmetric channel |
| title_full_unstemmed | Neural network recognition system for video transmitted through a binary symmetric channel |
| title_short | Neural network recognition system for video transmitted through a binary symmetric channel |
| title_sort | neural network recognition system for video transmitted through a binary symmetric channel |
| topic | neural networks video recognition yolo binary symmetric channel video denoise |
| url | https://www.computeroptics.ru/eng/KO/Annot/KO48-4/480413e.html |
| work_keys_str_mv | AT vababoshina neuralnetworkrecognitionsystemforvideotransmittedthroughabinarysymmetricchannel AT arorazaev neuralnetworkrecognitionsystemforvideotransmittedthroughabinarysymmetricchannel AT palyakhov neuralnetworkrecognitionsystemforvideotransmittedthroughabinarysymmetricchannel AT eeboyarskaya neuralnetworkrecognitionsystemforvideotransmittedthroughabinarysymmetricchannel |