| DC Field | Value | Language |
|---|
| dc.contributor.author | Kharinov, M. | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2024-03-01T07:48:15Z | - |
| dc.date.available | 2024-03-01T07:48:15Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.citation | Kharinov, M. About Computer Vision using Optimal Image Approximations / M. Kharinov // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 305–311. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/54452 | - |
| dc.description.abstract | This paper presents the priority results of
interdisciplinary SPC RAS research in the areas of cluster
analysis and object detection in a digital image. For a specific
domain of video data, the NP-hard problem of estimating
optimal piecewise constant image approximations, which are
characterized by possibly minimal approximation errors (total
squared errors) for each number of 1, 2... etc colors, is posed
and solved. The novelty of just this paper is in the presentation
of accelerating the calculation of optimal image
approximations. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | BSU | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | image processing | en_US |
| dc.subject | big data cluster analysis | en_US |
| dc.subject | Sleator-Tarjan dynamic trees | en_US |
| dc.title | About Computer Vision using Optimal Image Approximations | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)
|
