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DDSP and NEWT papers don't mention it, but RAVE does: "We use dequantization, random crop and allpass filters with random coefficients as our data augmentation strategy."
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Hello author, have you considered using mosaic data enhancement operations in face detection?
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Prioritize fast, GPU-based audio augmentations that maintain the vocal content. I'd like to use nnAudio for the spectogram computation, so augmentations that use PyTorch modules are ideal.
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**Description:** The current Convolutional Neural Network (CNN) model for terrain classification is functional, but there are several areas for improvement to boost performance and efficiency. These o…
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[Graph contrastive learning with augmentations](https://proceedings.neurips.cc/paper_files/paper/2020/hash/3fe230348e9a12c13120749e3f9fa4cd-Abstract.html)
```bib
@article{you2020graph,
title={Gra…
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When I was running fine_tune.sh, I came across the error "hydra.errors.OverrideParseException: mismatched input '=' expecting ". My shell file is as below:
#!/bin/bash
export HYDRA_FULL_ERROR=1
…
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### Search before asking
- [X] I have searched the HUB [issues](https://github.com/ultralytics/hub/issues) and [discussions](https://github.com/ultralytics/hub/discussions) and found no similar quest…
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Hi@LBH1024, it seems that the code about data augmentation is missing, which is essential to get better performance, can you share this code? Thanks!
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I read your paper,The Table I show the number of data after data augmentation,but l don't see in the code.