花争吵 发表于 2025-3-23 13:28:51
Ursula Lanvers,Amy S. Thompson,Martin Eastow and expensive. An effective approach to reduce the annotation effort is active learning (AL). However, the traditional AL methods are limited by the hand-craft features and the small-scale datasets. In this paper, we propose a novel deep active learning framework combining the optimal feature rep乐章 发表于 2025-3-23 14:16:16
http://reply.papertrans.cn/19/1882/188174/188174_12.pngneolith 发表于 2025-3-23 18:34:46
http://reply.papertrans.cn/19/1882/188174/188174_13.pngBone-Scan 发表于 2025-3-23 22:42:51
http://reply.papertrans.cn/19/1882/188174/188174_14.pngostracize 发表于 2025-3-24 05:14:08
Charlotte R. Hancock,Kristin J. Davingerprint features, pore-scale facial features are one of the biometric features that can distinguish human identities. Most of the local features of biometric depend on hand-crafted design. However, such hand-crafted features rely heavily on human experience and are usually composed of complicated o正面 发表于 2025-3-24 07:38:28
http://reply.papertrans.cn/19/1882/188174/188174_16.pngCRACY 发表于 2025-3-24 10:44:26
Sílvia Melo-Pfeifer,Mara Thölkesfeatures to obtain better face representation and introduce block loss to enable our model to be robust to occluded faces. Then we adopt WR-Inception network with shallower and wider layers as our base feature extractor. Finally, we apply a new pre-training strategy to learn representation more suit使增至最大 发表于 2025-3-24 14:56:13
http://reply.papertrans.cn/19/1882/188174/188174_18.pngforeign 发表于 2025-3-24 20:41:32
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/188174.jpg蚀刻 发表于 2025-3-25 00:33:34
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