deactivate
发表于 2025-3-23 10:48:59
http://reply.papertrans.cn/24/2343/234266/234266_11.png
PLE
发表于 2025-3-23 16:59:02
,SSBNet: Improving Visual Recognition Efficiency by Adaptive Sampling,SSB-ResNet-RS-200 achieved 82.6% accuracy on ImageNet dataset, which is 0.6% higher than the baseline ResNet-RS-152 with a similar complexity. Visualization shows the advantage of SSBNet in allowing different layers to focus on different positions, and ablation studies further validate the advantage
起皱纹
发表于 2025-3-23 18:38:03
,Filter Pruning via Feature Discrimination in Deep Neural Networks, our method first selects relatively redundant layers by hard and soft changes of the network output, and then prunes only at these layers. The whole process dynamically adjusts redundant layers through iterations. Extensive experiments conducted on CIFAR-10/100 and ImageNet show that our method ach
没血色
发表于 2025-3-24 00:26:44
http://reply.papertrans.cn/24/2343/234266/234266_14.png
衍生
发表于 2025-3-24 05:58:08
,Interpretations Steered Network Pruning via Amortized Inferred Saliency Maps,roducing a selector model that predicts real-time smooth saliency masks for pruned models. We parameterize the distribution of explanatory masks by Radial Basis Function (RBF)-like functions to incorporate geometric prior of natural images in our selector model’s inductive bias. Thus, we can obtain
nuclear-tests
发表于 2025-3-24 07:38:29
The Reforms: Experiences and Failuresce values by regulating the contributions of individual examples in the parameter update of the network. Further, our algorithm avoids redundant labeling by promoting diversity in batch selection through propagating the confidence of each newly labeled example to the entire dataset. Experiments invo
arbovirus
发表于 2025-3-24 11:39:32
http://reply.papertrans.cn/24/2343/234266/234266_17.png
使更活跃
发表于 2025-3-24 16:26:01
International Economic Relationsependencies without self-attention. Extensive experiments demonstrate that our adaptive weight mixing is more efficient and effective than previous weight generation methods and our AMixer can achieve a better trade-off between accuracy and complexity than vision Transformers and MLP models on both
不遵守
发表于 2025-3-24 23:03:46
Reintegrating the World Economy pretrained model with computation and parameter constraints. Comprehensive experiments demonstrate the efficacy of TinyViT. It achieves a top-1 accuracy of 84.8% on ImageNet-1k with only 21M parameters, being comparable to Swin-B pretrained on ImageNet-21k while using 4.2 times fewer parameters. Mo
jeopardize
发表于 2025-3-25 02:22:01
http://reply.papertrans.cn/24/2343/234266/234266_20.png