August 27, 2019 - Bag of Tricks in Machine Learning

Image Classification Papers

August 27, 2019August 27, 2019 by admin

Preparation: CNN course by Andrew Ng

Convolutional Neural Networks | Coursera

ImageNet Leaderboard (read in reverse order)

State-of-the-art table for Image Classification on ImageNet

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Julien Plu @julienplu·

19h

Ever wanted to deploy the fast @TensorFlow models from @huggingface Transformers in TensorFlow Serving? Check out the following:
Tutorial: https://huggingface.co/blog/tf-serving
Notebook: https://tinyurl.com/y6r5ch2v

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Graham Neubig @gneubig·

20 Jan

If you're looking for some nice videos on cutting-edge NLP research, check out the @LTIatCMU YouTube Channel with presentations by LTI members and guest speakers! https://www.youtube.com/c/LTIatCMU

我们的中国朋友也可以观看bilibili：https://space.bilibili.com/1377044784

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Gregory Koberger @gkoberger·

18 Jan

Now this is patience....

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arXiv in review @arxiv_in_review·

7 Jan

#NeurIPS2020 Parameterized Explainer for Graph Neural Network. (arXiv:2011.04573v1 [cs\.LG] CROSS LISTED) http://arxiv.org/abs/2011.04573

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Facebook AI@facebookai·

24 Dec

We’re open-sourcing a new system to train computer vision models using Transformers. Data-efficient image Transformers (DeiT) is a high-performance image classification model requiring less data & computing resources to train than previous AI models. https://ai.facebook.com/blog/data-efficient-image-transformers-a-promising-new-technique-for-image-classification/

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