表两个
发表于 2025-3-26 21:12:52
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减震
发表于 2025-3-27 03:55:49
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Critical
发表于 2025-3-27 06:04:04
Pamfili Antipa,Rémy Lecat the foundation for global context extraction. Secondly, we construct a Global Perception Module (GPM) for global context modeling through pixel-level correspondence, which employs a global sliding weighted technique to provide the network with rich semantics and acts on each layer to enhance SOD pe
linear
发表于 2025-3-27 09:43:20
Thomas A. Knetschrates the proximity between suboptimal samples and positive samples as new loss term, so as to devise the one-dimensional spatial constraint ComPreHensive L1 Loss (CPH L1 Loss) and the two-dimensional spatial constraint ComPreHensive Generalized Intersection over Union Loss (CPH GIoU Loss). The appr
酷热
发表于 2025-3-27 14:07:44
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字的误用
发表于 2025-3-27 20:31:31
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啜泣
发表于 2025-3-27 23:46:11
ptors to make predictions. Based on the observation in this paper, we find and empirically demonstrate that such features, when extracted from the ViT model, consistently improve the classification performance. Moreover, we observe that the pre-trained ViT which is fine-tuned on specific dataset is
Intend
发表于 2025-3-28 04:12:29
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恩惠
发表于 2025-3-28 07:27:41
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Admire
发表于 2025-3-28 10:58:52
Antonio Bassanetti,Francesco Zollinof the CNN was based on EEGNet. The performance of the multi-modal approach was compared to mono-modal baselines (based on EEG or EMG only). The multi-modal EEG+EMG pipeline outperformed the EEG-based pipeline during movement initiation, while it outperformed the EMG-based pipeline in motor preparati