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Hello,
I have been experimenting with replacing the standard convolutions in the VGG model with DO-Conv (Depthwise Separable Convolution). However, I am facing an issue where the loss does not decr…
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In your paper , I saw a result of ResNet50-dcls given besides the ConvNeXt-dcls. But I didn't find the trained model. If I need to train it by myself,Could you give the setting about it?Thank you
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### Search before asking
- [X] I have searched the YOLOv8 [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussions) and fou…
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Hello,
in the beginning, I would like to say that this library is beautiful, and I'm really impressed by how good it works. I mean how precise.
I have an issue with the speed of face and landmark…
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- Knowledge Distillation, involves training a smaller, simpler model (student) to learn from a larger, more complex model (teacher) in a way that the student captures both the teacher's accurate predi…
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Great job!
I found that the deformconv1d in this repo is different from the original one. If I'm right, the deformable kernel will not change when facing different inputs. Since the offsets are set a…
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Hello, I'm quite interested in the section about LSTM, but I'm still trying to understand how the "plain LSTM cell" mentioned in the paper is actually applied. It seems like the backbone network utili…
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### Here are some suggestions for modifying the encoder and decoder components of the ENet, ICNet, and BiSeNet models:
**ENet:**
> Encoder Modification:
> Increase the depth of the encoder by a…
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https://arxiv.org/pdf/1706.03059.pdf
概要:
xceptionやmobilenetで使われた depse-wise-convolutionを
1D-convにも適用し(語順方向とchannel方向にseparatable)
それをencoder、decoderに使うことで、NMTでSOTA
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Sik-Ho Tang. [Review: Xception — With Depthwise Separable Convolution, Better Than Inception-v3 (Image Classification)](https://towardsdatascience.com/review-xception-with-depthwise-separable-convolut…