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Hello, Alexey!
Do you have plans to implement such feature, so it will be possible to visualise what the network has learnt, or which parts of an input image are most characteristic of certain class?…
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In `Guided backpropagation`,
Error:
```
KeyError: "The name 'predictions_10/Softmax:0' refers to a Tensor which does not exist. The operation, 'predictions_10/Softmax', does not exist in the grap…
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@conan7882 thanks for your great work.
While I have an implementation issue in guided_backpropagation.py
I install tensorcv-0.0.5, tensorcv-0.1.0 and tensorcv-0.2.0
but however could not find this…
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# 論文リンク
https://arxiv.org/abs/2001.01037
# 公開日（yyyy/mm/dd）
2020/01/04
# 概要
Attenstion を用いた image captioning に合わせて開発した
> variants of layer-wise
relevance backpropagation (LRP) and gradient…
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## 一言でいうと
CNNモデルの出力結果に対する可視化手法であるGrad-CAMの提案。入力画像に対する注目領域の可視化を行う。image captioningやvisual question answering(VQA)モデルにも適用可能。
行われている操作は以下のとおり。
(1) guided backpropagationで得られたサリエンシーマップを作成
(2) target c…
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Hey, thanks for your excellent work!
I noticed that in your paper, you gave the visualized interpretation which help us understand what the network learned.
For this interesting result, I wanna …
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RuntimeError Traceback (most recent call last)
in
9 # Ready to roll!
10
---> 11 backprop.visualize(owl, target_class, guided=True)
~\Downloads\flashto…
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Hi, I have found that with pytorch 1.13 and 2.0 (not with pytorch
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## 🐛 Bug
We have a use-case in Captum in which we need to use a forward hook to extract an intermediate layer activation and then use torch.autograd.grad to compute gradients of this activation wit…
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Hi Koen,
I have read your some papers about bspline transformation for medical image analysis. However, I'm still not sure how to change the bspline transformation operations into a neural n…