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related paper
|摘要|
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|Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those us…
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https://arxiv.org/abs/1512.03385
> Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than t…
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Interest: 2
URL: https://arxiv.org/pdf/1710.10348.pdf
Keyword: ResNet Analysis
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https://arxiv.org/pdf/1512.03385.pdf
Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than…
leo-p updated
7 years ago
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Dear authors,
I recently read your outstanding paper titled "Boosting Residual Networks with Group Knowledge" and was thoroughly impressed by your innovative approach. The methods and results prese…
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Thank you for your brilliant work. Could you help me with this problem when trying demo? I've re-downloaded models from both baiduyun and get_models.sh
sure@sure-ThinkStation-P318:~/文档/sure/pose/ac…
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As the name suggests, the skip connections in deep architecture bypass some of the neural network layers and feed the output of one layer as the input to the following levels. It is a standard module …
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hello,when I run "python main.py recognition -c config/st_gcn/kinetics-skeleton/test.yaml",the following error occurred:
[06.20.19|20:28:58] Load weights from ./models/st_gcn.kinetics.pt.
[06.20.19|…
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related paper
|摘要|
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|The trend towards increasingly deep neural networks has been driven by a general observation that increasing depth increases the performance of a network. Recently, howe…
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- KaimingHe/deep-residual-networks issues/39
- Support ResNet reference models for ILSVRC (beniz/deepdetect pull/60)