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Update README.md
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@mansishr
mansishr committed Oct 7, 2021
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Expand Up @@ -13,9 +13,9 @@ Two neural networks are used: an encoder and a classifier. The encoder is compos
The encoder has a hierarchical structure. The receptive field of the encoder is K = 64, and that of the embedded smaller encoder is K = 32. Patch SVDD divides the images into patches with a size K and a stride S. The values for the strides are S = 16 and S = 4 for the encoders with K = 64 and K = 32, respectively.

### 3. Links
# [Original paper](https://arxiv.org/abs/2006.16067)
# [Original Github code](https://github.com/nuclearboy95/Anomaly-Detection-PatchSVDD-PyTorch/tree/934d6238e5e0ad511e2a0e7fc4f4899010e7d892)
# [MVTec ad dataset download link](ftp://guest:GU.205dldo@ftp.softronics.ch/mvtec_anomaly_detection/mvtec_anomaly_detection.tar.xz)
1. [Original paper](https://arxiv.org/abs/2006.16067)
2. [Original Github code](https://github.com/nuclearboy95/Anomaly-Detection-PatchSVDD-PyTorch/tree/934d6238e5e0ad511e2a0e7fc4f4899010e7d892)
3. MVTec ad dataset download link (ftp://guest:GU.205dldo@ftp.softronics.ch/mvtec_anomaly_detection/mvtec_anomaly_detection.tar.xz)

### 4. How to run this tutorial (without TLC and locally as a simulation):

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