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pro vyhledávání: '"Yasufumi Kawano"'
Autor:
Yasufumi Kawano, Yoshimitsu Aoki
Publikováno v:
IEEE Access, Vol 12, Pp 127283-127293 (2024)
Semantic segmentation is essential in computer vision for various applications, yet traditional approaches face significant challenges, including the high cost of annotation and extensive training for supervised learning. Additionally, due to the lim
Externí odkaz:
https://doaj.org/article/49a594e5c6aa4056adaada7095ffdffc
Autor:
Yasufumi Kawano, Yoshimitsu Aoki
Publikováno v:
IEEE Access, Vol 12, Pp 88322-88331 (2024)
Semantic segmentation is a crucial task in computer vision, where each pixel in an image is classified into a category. However, traditional methods face significant challenges, including the need for pixel-level annotations and extensive training. F
Externí odkaz:
https://doaj.org/article/a25306a72b1446179c2fe36fdb3fd247
Publikováno v:
Sensors, Vol 22, Iss 14, p 5244 (2022)
One way to improve annotation efficiency is active learning. The goal of active learning is to select images from many unlabeled images, where labeling will improve the accuracy of the machine learning model the most. To select the most informative u
Externí odkaz:
https://doaj.org/article/edcaea98a6ce4bbbacad2467668e5506
Publikováno v:
Journal of the Japan Society for Precision Engineering. 88:211-216
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59bb7dc392f8fb6eefd76926be8eba6d
https://doi.org/10.2493/jjspe.88.211
https://doi.org/10.2493/jjspe.88.211