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Imbalanced dataset is relevant primarily in the context of supervised machine lea…
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# Data Augmentation in Emotion Classification Using Generative Adversarial Networks #
- Author: Xinyue Zhu, Yifan Liu, Zengchang Qin, Jiahong Li
- Origin: https://arxiv.org/abs/1711.00648
- Relat…
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|paper| [Multi-Conditioning and Data Augmentation Using Generative Noise Model for Speech Emotion Recognition in Noisy Conditions](https://ieeexplore.ieee.org/abstract/document/90…
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The following papers help guide our work. The techniques and experiments we hope to leverage for our study are well explained in these papers.
- [[2307.16833] Data Augmentation for Neural Machine Tra…
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1. 如果object bank是单数据集内(train或val)的,在test上提升这么明显,那这个方法确实很有价值。
2. 如果有跨数据集object或者含有test data object(正常来讲不太可能),那应该标明使用了额外的数据(add data),实际价值可能会打折,有点像跨数据集增强的思路。
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https://doi.org/10.1101/390153
> A fundamental problem in biomedical research is the low number of observations available, mostly due to a lack of available biosamples, prohibitive costs, or ethica…
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It seems that the augment comes from "Training Generative Adversarial Networks with Limited Data", But I am confused what 'augment_p' and 'ada_target' and 'ada_length' means. Can I use these augmentat…
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- #701
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#### Learning Goals
- Get hands-on experience with generative modeling
- Use convolutional neural networks with PyTorch
- Learn the foundations of the concepts used to create deep fakes
### Ex…
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MIT-SelefDriving Course 笔记
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1. Difference between ML(Machine Learning) & DL (Deep Learning)
- ML: input -> Feature extractoiin (human beings to do that) -> …
Iranb updated
5 years ago