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Layer-Wise Network Compression Using Gaussian Mixture Model

https://doi.org/10.3390/electronics10010072

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks

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RMNv2: Reduced Mobilenet V2 for CIFAR10

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Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

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Going deeper with convolutions

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Fully convolutional networks for semantic segmentation

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Deep Residual Learning for Image Recognition

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A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning

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Weighted-Entropy-Based Quantization for Deep Neural Networks

inferredcites →https://doi.org/10.1109/cvpr.2018.00716openalex-snapshot

ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices

inferredcites →https://doi.org/10.1109/cvpr.2018.00958openalex-snapshot

NISP: Pruning Networks Using Neuron Importance Score Propagation

inferredcites →https://doi.org/10.1109/cvpr.2019.00447openalex-snapshot

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration

inferredcites →https://doi.org/10.1109/iccv.2015.169openalex-snapshot

Fast R-CNN

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Learning Efficient Convolutional Networks through Network Slimming

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ThiNet: A Filter Level Pruning Method for Deep Neural Network Compression

inferredcites →https://doi.org/10.1109/iccv.2019.00381openalex-snapshot

Be Your Own Teacher: Improve the Performance of Convolutional Neural Networks via Self Distillation

inferredcites →https://doi.org/10.1109/icip.2019.8803025openalex-snapshot

ACNET: Attention Based Network to Exploit Complementary Features for RGBD Semantic Segmentation

inferredcites →https://doi.org/10.1109/tits.2020.3023331openalex-snapshot

Omnisupervised Omnidirectional Semantic Segmentation

inferredcites →https://doi.org/10.1109/tpami.2016.2644615openalex-snapshot

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

inferredcites →https://doi.org/10.1609/aaai.v34i04.5963openalex-snapshot

Improved Knowledge Distillation via Teacher Assistant

inferredcites →https://doi.org/10.24963/ijcai.2018/453openalex-snapshot

Improving Deep Neural Network Sparsity through Decorrelation Regularization

inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot

Very Deep Convolutional Networks for Large-Scale Image Recognition

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FitNets: Hints for Thin Deep Nets

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Deep Learning with Limited Numerical Precision

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Distilling the Knowledge in a Neural Network

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Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

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ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

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Variational Dropout Sparsifies Deep Neural Networks

inferredcites →https://doi.org/10.48550/arxiv.1705.07565openalex-snapshot

Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon

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The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

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Discrimination-aware Channel Pruning for Deep Neural Networks

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EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Pruning networks at once via nuclear norm-based regularization and bi-level optimization

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T-EAP: Trainable Energy-Aware Pruning for NVM-based Computing-in-Memory Architecture

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Optimization Methods of Deep Neural Networks on Automotive Embedded Computing Systems

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Constraints-Aware Trainable Pruning With System Optimization For The On-Demand Offloading Edge-Cloud Collaborative System

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Model Parallelism Optimization for Distributed DNN Inference on Edge Devices

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Pruning from Scratch via Shared Pruning Module and Nuclear norm-based Regularization

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SAMPLE-BASED DYNAMIC HIERARCHICAL TRANSFORMER WITH LAYER AND HEAD FLEXIBILITY VIA CONTEXTUAL BANDIT

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High-Performance and Lightweight AI Model for Robot Vacuum Cleaners with Low Bitwidth Strong Non-Uniform Quantization

inferred← citeshttps://doi.org/10.3390/electronics11060945openalex-snapshot

A Survey on Efficient Convolutional Neural Networks and Hardware Acceleration

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A Novel Deep Learning Model Compression Algorithm

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Quantization and Deployment of Deep Neural Networks on Microcontrollers

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Lossless Reconstruction of Convolutional Neural Network for Channel-Based Network Pruning

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A Comprehensive Review of Hardware Acceleration Techniques and Convolutional Neural Networks for EEG Signals

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MicroAI : embedded artificial intelligence for human activity recognition on smart glasses

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Inference acceleration and optimization in deep neural networks for computer vision

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