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adding TResNet: High Performance GPU-Dedicated Architecture #9

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adding TResNet: High Performance GPU-Dedicated Architecture #9

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TResNet: High Performance GPU-Dedicated Architecture
mrT23 Apr 3, 2020
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mrT23 Apr 3, 2020
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Expand Up @@ -208,6 +208,7 @@ Okay, signal processing might not be directly related to deep learning, but stud
- [Densely Connected Convolutional Networks](https://arxiv.org/pdf/1608.06993.pdf) - Best Paper Award at CVPR 2017, yielding improvements on state-of-the-art performances on CIFAR-10, CIFAR-100 and SVHN datasets, this new neural network architecture is named DenseNet.
- [The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation](https://arxiv.org/pdf/1611.09326.pdf) - Merges the ideas of the U-Net and the DenseNet, this new neural network is especially good for huge datasets in image segmentation.
- [Prototypical Networks for Few-shot Learning](https://arxiv.org/pdf/1703.05175.pdf) - Use a distance metric in the loss to determine to which class does an object belongs to from a few examples.
- [TResNet: High Performance GPU-Dedicated Architecture](https://github.com/mrT23/TResNet) - TResNet models were designed and optimized to give the best speed-accuracy tradeoff out there on GPUs.

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