Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Wurui Shi"'
Publikováno v:
IEEE Access, Vol 12, Pp 67246-67255 (2024)
The mainstream Go AI algorithms represented by AlphaZero and KataGo suffer from low-quality samples in the early training period and low exploration efficiency when performing traditional Monte Carlo Tree Search (MCTS). For the shortcomings mentioned
Externí odkaz:
https://doaj.org/article/f9cc070602d845d08e48ed9781481348
Publikováno v:
IEEE Access, Vol 10, Pp 134263-134276 (2022)
Fusing features from different layers is essential to improve the ship target detection ability in the synthetic aperture radar (SAR) images. Mainstream methods usually perform simple addition or concatenation operations on adjacent feature layers wi
Externí odkaz:
https://doaj.org/article/a157a646228e4700929255586673027f
Publikováno v:
IEEE Access, Vol 10, Pp 77872-77882 (2022)
The study of face frontalization is essential for improving face recognition accuracy in extreme pose scenarios. Mainstream methods like TP-GAN, CAPG-GAN, etc., have made meaningful contributions. However, they still suffer from two problems: the lac
Externí odkaz:
https://doaj.org/article/be2a72fdd2b5465fbfa45b7c718adedc
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
Road detection based on remote sensing images is of great significance to intelligent traffic management. The performances of the mainstream road detection methods are mainly determined by their extracted features, whose richness and robustness can b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f47ace2002ad8b53e80faf89a296c51
https://doi.org/10.1109/lgrs.2022.3198077
https://doi.org/10.1109/lgrs.2022.3198077
Publikováno v:
IEEE Access. :1-1
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bec69efa36883f1cd268a10515f8be47
https://doi.org/10.1109/access.2023.3244320
https://doi.org/10.1109/access.2023.3244320