Understanding Deep Architectures using a Recursive Convolutional Network

6 December 2013

Papers citing "Understanding Deep Architectures using a Recursive Convolutional Network"

26 / 26 papers shown

Title
Relaxed Recursive Transformers: Effective Parameter Sharing with Layer-wise LoRA Sangmin Bae Adam Fisch Hrayr Harutyunyan Ziwei Ji Seungyeon Kim Tal Schuster KELM 84 5 0 28 Oct 2024
Latent Iterative Refinement for Modular Source Separation Dimitrios Bralios Efthymios Tzinis G. Wichern Paris Smaragdis Jonathan Le Roux BDL 33 5 0 22 Nov 2022
VSpSR: Explorable Super-Resolution via Variational Sparse Representation Hang Zhou Chao Huang Shangqi Gao Xiahai Zhuang 33 6 0 17 Apr 2021
Multiscale Deep Equilibrium Models Shaojie Bai V. Koltun J. Zico Kolter BDL 38 211 0 15 Jun 2020
An Overview of Neural Network Compression James OÑeill AI4CE 45 98 0 05 Jun 2020
Joint-SRVDNet: Joint Super Resolution and Vehicle Detection Network Moktari Mostofa Syeda Nyma Ferdous B. Riggan Nasser M. Nasrabadi SupR 14 38 0 03 May 2020
Cross-X Learning for Fine-Grained Visual Categorization W. Luo Xitong Yang Xianjie Mo Yuheng Lu L. Davis Jun Li Jian Yang Ser-Nam Lim 85 193 0 10 Sep 2019
A Coarse-to-Fine Multi-stream Hybrid Deraining Network for Single Image Deraining Yanyan Wei Zhao Zhang Haijun Zhang Richang Hong Meng Wang 19 35 0 28 Aug 2019
Multi-scale deep neural networks for real image super-resolution Yuxin Li Xiahai Zhuang SupR 24 33 0 24 Apr 2019
Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks Domen Tabernik Matej Kristan A. Leonardis 16 22 0 20 Feb 2019
A Deeply-Recursive Convolutional Network for Crowd Counting Xinghao Ding Zhirui Lin Fujin He Yu Wang Yue Huang 11 51 0 15 May 2018
Towards Principled Design of Deep Convolutional Networks: Introducing SimpNet S. H. HasanPour Mohammad Rouhani Mohsen Fayyaz Mohammad Sabokrou Ehsan Adeli 50 45 0 17 Feb 2018
Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning? Nima Tajbakhsh Jae Y. Shin S. Gurudu R. T. Hurst Christopher B. Kendall Michael B. Gotway Jianming Liang 19 2,497 0 02 Jun 2017
Deep Architectures for Modulation Recognition Nathan E. West Tim O'Shea 19 401 0 27 Mar 2017
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 297 10,225 0 16 Nov 2016
Do semantic parts emerge in Convolutional Neural Networks? Abel Gonzalez-Garcia Davide Modolo V. Ferrari 158 113 0 13 Jul 2016
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex Q. Liao T. Poggio 213 255 0 13 Apr 2016
Do Deep Convolutional Nets Really Need to be Deep and Convolutional? G. Urban Krzysztof J. Geras Samira Ebrahimi Kahou Ozlem Aslan Shengjie Wang R. Caruana Abdel-rahman Mohamed Matthai Philipose Matthew Richardson 20 47 0 17 Mar 2016
Representation of linguistic form and function in recurrent neural networks Ákos Kádár Grzegorz Chrupała A. Alishahi 27 162 0 29 Feb 2016
Deeply-Recursive Convolutional Network for Image Super-Resolution Jiwon Kim Jung Kwon Lee Kyoung Mu Lee SupR 55 2,491 0 14 Nov 2015
Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks Zhen Zuo Bing Shuai G. Wang Xiao Liu Xingxing Wang B. Wang 16 93 0 13 Sep 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 29 18,455 0 06 Feb 2015
Convolutional Neural Networks at Constrained Time Cost Kaiming He Jian Sun 3DV 27 1,288 0 04 Dec 2014
Learning Deep Structured Models Liang-Chieh Chen A. Schwing Alan Yuille R. Urtasun BDL 35 247 0 09 Jul 2014
Do Deep Nets Really Need to be Deep? Lei Jimmy Ba R. Caruana 67 2,107 0 21 Dec 2013
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,638 0 03 Jul 2012