Zobrazeno 1 - 10
of 593
pro vyhledávání: '"Foreground-background"'
Publikováno v:
Meteorological Applications, Vol 31, Iss 1, Pp n/a-n/a (2024)
Abstract Lightning often causes death, injury, and damage to various facilities and equipment. Accurately detecting the spatial location of lightning occurrence by predicting thunderstorms and lightning is of great significance. Traditional lightning
Externí odkaz:
https://doaj.org/article/753a217dfcb649ce838c975804934710
Publikováno v:
IEEE Access, Vol 11, Pp 36516-36537 (2023)
As a fundamental branch in cross-modal retrieval, image-text retrieval is still a challenging problem largely due to the complementary and imbalanced relationship between different modalities. However, existing works have not effectively scanned and
Externí odkaz:
https://doaj.org/article/6b1c9f4317a14147988f8907c852b24d
Publikováno v:
Applied Sciences, Vol 14, Iss 7, p 2844 (2024)
Unsupervised Domain Adaptative Object Detection (UDAOD) aims to alleviate the gap between the source domain and the target domain. Previous methods sought to plainly align global and local features across domains but adapted numerous pooled features
Externí odkaz:
https://doaj.org/article/037bb4d89ce74a61bf61c22533e80cf0
Akademický článek
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Publikováno v:
IEEE Access, Vol 9, Pp 103927-103936 (2021)
This paper proposes a depth from light field (DFLF) method specifically to deal with occlusion based on the foreground-background separation (FBS). The FBS-based methods infer the disparity maps by accumulating the binary maps which divide whether ea
Externí odkaz:
https://doaj.org/article/c3371cd4bd0b4a488c90c6ccf4244774
Publikováno v:
IEEE Open Journal of Signal Processing, Vol 1, Pp 274-286 (2020)
Moving object detection in a given video sequence is a pivotal step in many computer vision applications such as video surveillance. Robust Principal Component Analysis (RPCA) performs low-rank and sparse decomposition to accomplish such a task when
Externí odkaz:
https://doaj.org/article/3f53c609cc634fa58ebd37afdf4614bd
Publikováno v:
IEEE Access, Vol 8, Pp 84217-84229 (2020)
Low-rank and sparse decomposition (LRSD) has attracted wide attention in video foreground-background separation and many other fields. However, the traditional LRSD methods have many tough problems, such as the problems of the low accuracy of the sur
Externí odkaz:
https://doaj.org/article/467f46c614d5495cb4702d983be79b9d
Publikováno v:
IEEE Access, Vol 8, Pp 88259-88272 (2020)
Foreground-background separation of surveillance video, that models static background and extracts moving foreground simultaneously, attracts increasing attentions in building a smart city. Conventional techniques towards this always consider the bac
Externí odkaz:
https://doaj.org/article/37814cf9d2bb4eeaa924bc785a37757f