DO-Conv: Depthwise Over-parameterized Convolutional Layer

DO-Conv: Depthwise Over-parameterized Convolutional Layer

22 June 2020

Dani Lischinski

Daniel Cohen-Or

Papers citing "DO-Conv: Depthwise Over-parameterized Convolutional Layer"

7 / 7 papers shown

Title
Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency Vithursan Thangarasa Shreyas Saxena Abhay Gupta Sean Lie 23 3 0 21 Mar 2023
Utilizing Excess Resources in Training Neural Networks Amit Henig Raja Giryes 34 0 0 12 Jul 2022
Online Convolutional Re-parameterization Mu Hu Junyi Feng Jiashen Hua Baisheng Lai Jianqiang Huang Xiaojin Gong Xiansheng Hua 11 26 0 02 Apr 2022
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 36 16 0 05 Dec 2021
Fuzzy-Depth Objects Grasping Based on FSG Algorithm and a Soft Robotic Hand Hanwen Cao Junda Huang Yichuan Li Jianshu Zhou Yunhui Liu 14 7 0 21 Oct 2021
RepVGG: Making VGG-style ConvNets Great Again Xiaohan Ding X. Zhang Ningning Ma Jungong Han Guiguang Ding Jian-jun Sun 130 1,546 0 11 Jan 2021
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 294 10,216 0 16 Nov 2016