Network Decoupling: From Regular to Depthwise Separable Convolutions

Network Decoupling: From Regular to Depthwise Separable Convolutions

16 August 2018

Papers citing "Network Decoupling: From Regular to Depthwise Separable Convolutions"

11 / 11 papers shown

Title
TinyAD: Memory-efficient anomaly detection for time series data in Industrial IoT Yuting Sun Tong Chen Quoc Viet Hung Nguyen Hongzhi Yin 23 12 0 07 Mar 2023
Semi-tensor Product-based TensorDecomposition for Neural Network Compression Hengling Zhao Yipeng Liu Xiaolin Huang Ce Zhu 44 6 0 30 Sep 2021
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration Shiwei Liu Tianlong Chen Xiaohan Chen Zahra Atashgahi Lu Yin Huanyu Kou Li Shen Mykola Pechenizkiy Zhangyang Wang D. Mocanu 34 111 0 19 Jun 2021
Measuring the Ripeness of Fruit with Hyperspectral Imaging and Deep Learning Leon Amadeus Varga J. Makowski A. Zell 11 20 0 20 Apr 2021
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 31 79 0 17 Sep 2020
Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets D. Haase Manuel Amthor 20 132 0 30 Mar 2020
Cluster Pruning: An Efficient Filter Pruning Method for Edge AI Vision Applications Chinthaka Gamanayake Lahiru Jayasinghe Benny Kai Kiat Ng Chau Yuen VLM 23 45 0 05 Mar 2020
Decomposable-Net: Scalable Low-Rank Compression for Neural Networks A. Yaguchi Taiji Suzuki Shuhei Nitta Y. Sakata A. Tanizawa 19 9 0 29 Oct 2019
Depth-wise Decomposition for Accelerating Separable Convolutions in Efficient Convolutional Neural Networks Yihui He Jianing Qian Jianren Wang Cindy X. Le Congrui Hetang Qi Lyu Wenping Wang Tianwei Yue 45 11 0 21 Oct 2019
sharpDARTS: Faster and More Accurate Differentiable Architecture Search Andrew Hundt Varun Jain Gregory Hager OOD 30 66 0 23 Mar 2019
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 271 5,329 0 05 Nov 2016