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Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network

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Jan 21 2020 Jeremy Howard

This is a very interesting paper. It shows that a tweaked ResNet50 is about as accurate as EfficientNet-B4 but >3x faster. The EfficientNet paper measured FLOPS, which is a theoretical performance measure, rather than time, which is what actually matters. https://arxiv.org/abs/2001.06268 https://t.co/cyBiueqPuf
10 replies, 657 likes


Jan 22 2020 Daisuke Okanohara

A variety of techniques (architecture and regularization) have been proposed for improving CNNs. Assembling these techniques carefully to optimize accuracy and throughput enables ResNet to achieve similar accuracy as EfficientNet while 3x~10x throughput. https://arxiv.org/abs/2001.06268
0 replies, 11 likes


Jan 28 2020 Yann Dauphin

Combining Mixup and other recent techniques brings good old Resnet-50 from 76.3% to 82.79% on Imagenet AND the network has state-of-the-art efficiency. https://arxiv.org/pdf/2001.06268.pdf https://t.co/MwbusraUZr
0 replies, 6 likes


Jan 22 2020 那須音トウ | imenurok

Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network https://arxiv.org/abs/2001.06268
1 replies, 5 likes


Jan 21 2020 Morgan McGuire

Resnet-50 up to 82.8% top-1 imagenet accuracy 🤯 combo of architecture tweaks and regularisation "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network" - https://arxiv.org/pdf/2001.06268.pdf Hat-tip to fastai forums https://forums.fast.ai/t/fastai-v2-additional-models/62067/3
0 replies, 3 likes


Jan 27 2020 akira

https://arxiv.org/abs/2001.06268 Build the network ,that combines some powerful existing techniques, achieve same accuracy as EfficientNet B6 + AutoAug but 5 times faster. The authors say that the latest ones such as AugMix are not used here, so the accuracy may still be improved. https://t.co/J83LVHVxbP
0 replies, 2 likes


Jan 20 2020 arXiv CS-CV

Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network http://arxiv.org/abs/2001.06268
0 replies, 1 likes


Jan 28 2020 Nicolas Won

Check out our new paper "Compounding the performance accuracy of assembled techniques in a convolutional neural network". Our proposed ResNet-50 shows an improvement in top-1 accuracy from 76.3% to 82.78%. https://arxiv.org/abs/2001.06268
1 replies, 0 likes


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