-
-
# 🚀 Feature Request
I read the article "[SesameBERT: Attention for Anywhere](https://arxiv.org/pdf/1910.03176.pdf)" and would like to add SENet blocks in the Huggingface implementation. The article…
-
Thank you for sharing your very interesting work.
I have a question about the self-attention used in the conformer block.
Before applying the time_conformer, you reshape the tensor to a $(b \time…
-
Hi Wei Li. Thanks for sharing this great code! I learn a lot from it.
I found two error in SENet_Keras.py:
1, in line 77, you use y = add_common_layer(y). add_common_layer include BN and relu. from…
-
Hi @farmingyard ,
Have you tried combining SENet module with other popular structures (except Resnext), for instance, MobileNet, ShuffleNet etc.
thx!
-
It seems some of the nets define in models has some hidden bug.
For example, I use senet and will get CUDA out of memory error, but my batch_size is only 64, my GPU memory is 11G。
But when I use …
-
Some people have improved the structure of SENet to YOLOV3?
[https://github.com/hujie-frank/SENet](https://github.com/hujie-frank/SENet)
-
# Squeeze-and-Excitation Networks #
- Author: Jie Hu, Li Shen, Gang Sun
- Origin: https://arxiv.org/abs/1709.01507
- Related:
- http://image-net.org/challenges/talks_2017/SENet.pdf
- https:…
-
* https://arxiv.org/pdf/1709.01507.pdf
* https://github.com/hujie-frank/SENet
* https://github.com/taki0112/SENet-Tensorflow
-
Hi!
Fantastic work with the model and thank you for releasing the code!
I'd really appreciate if you could make available the weights after the model has been fine-tuned in speech enhancement on t…