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Updated by Patrice Kerremans on Dec 28, 2020
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Patrice Kerremans Patrice Kerremans
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The 9 Deep Learning Papers You Need To Know About

Listly by Patrice Kerremans

From the superb introduction to Convolutional Neural Networks guide "A Beginner's Guide To Understanding Convolutional Neural Networks" by "Adit Deshpande": "The 9 Deep Learning Papers You Need To Know About"
(If you count well you'll see there are 11 PDFs, not 9 :) )

Src: https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner's-Guide-To-Understanding-Convolutional-Neural-Networks/

1

Imagenet classification with deep convolutional neural network

Paper accepted and presented at the Neural Information Processing Systems Conference (http://nips.cc/)

2

Visualizing and Understanding Convolutional Networks

3

Very deep Convolutional Networks for large-scale image recognition

4

Going deeper with Convolutions

5

Deep Residual Learning for Image Recognition

6

Generative Aversarial Nets

7

Deep Visual-Semantic Alignments for Generating Image Descriptions

8

Spatial Transformer Networks

9

Rich feature hierarchies for accurate object detection and semantic segmentation

10

Fast R-CNN

11

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks