躺下残杀
发表于 2025-3-25 06:43:29
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figure
发表于 2025-3-25 09:47:47
Peter Bleses,Martin Seeleib-Kaiserrnels on learned representations is limited. In this work, we explore and employ the relationship between shape of kernels which define receptive fields (RFs) in CNNs for learning of feature representations and image classification. For this purpose, we present a feature visualization method for vis
aerial
发表于 2025-3-25 13:08:13
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用不完
发表于 2025-3-25 17:52:56
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AMITY
发表于 2025-3-25 22:20:28
Bastian Leibe,Jiri Matas,Max WellingIncludes supplementary material:
FUSC
发表于 2025-3-26 02:55:31
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234175.jpg
macrophage
发表于 2025-3-26 04:35:53
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Ascribe
发表于 2025-3-26 09:13:29
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genuine
发表于 2025-3-26 12:55:40
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Bucket
发表于 2025-3-26 18:33:06
Design of Kernels in Convolutional Neural Networks for Image Classificationed an outstanding performance in the classification task, comparing to a base CNN model that introduces more parameters and computational time, using the ILSVRC-2012 dataset [.]. Additionally, we examined the region of interest (ROI) of different models in the classification task and analyzed the ro