---
title: Deep Residual Learning for Image Recognition
tags: Memo
description: Deep Residual Networks
---

# Deep Residual Learning for Image Recognition

## Reading log/further reading

Papers:
- [Exploring Randomly Wired Neural Networks for Image Recognition](https://arxiv.org/abs/1904.01569)
- [Densely Connected Convolutional Networks](https://openaccess.thecvf.com/content_cvpr_2017/papers/Huang_Densely_Connected_Convolutional_CVPR_2017_paper.pdf)
- [Residual Networks are Exponential Ensembles of Relatively Shallow Networks](https://arxiv.org/abs/1605.06431v1)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929)
- [BlockDrop: Dynamic Inference Paths in Residual Networks](https://arxiv.org/abs/1711.08393)

Blogposts:
- [An Overview of ResNet and its Variants](https://towardsdatascience.com/an-overview-of-resnet-and-its-variants-5281e2f56035)

VGG parameter and memory usage

Naive Inception

Inception with bottleneck