Methods › General › Miscellaneous Components › Channel Shuffle
Channel Shuffle
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Channel Shuffle is an operation to help information flow across feature channels in convolutional neural networks. It was used as part of the ShuffleNet architecture.
If we allow a group convolution to obtain input data from different groups, the input and output channels will be fully related. Specifically, for the feature map generated from the previous group layer, we can first divide the channels in each group into several subgroups, then feed each group in the next layer with different subgroups.
The above can be efficiently and elegantly implemented by a channel shuffle operation: suppose a convolutional layer with g groups whose output has g ×n channels; we first reshape the output channel dimension into (g, n), transposing and then flattening it back as the input of next layer. Channel shuffle is also differentiable, which means it can be embedded into network structures for end-to-end training.
Papers archive 2025-07-28
30 shown of 80, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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Multispectral Detection Transformer with Infrared-Centric Sensor Fusion 21 May 2025 · 1 repository · arXiv:2505.15137
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Minimalistic Video Saliency Prediction via Efficient Decoder & Spatio Temporal Action Cues 1 Feb 2025 · 0 repositories · arXiv:2502.00397
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Comparison of Neural Models for X-ray Image Classification in COVID-19 Detection 8 Jan 2025 · 0 repositories · arXiv:2501.04196
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Advancing Green AI: Efficient and Accurate Lightweight CNNs for Rice Leaf Disease Identification 3 Aug 2024 · 0 repositories · arXiv:2408.01752
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Faster Metallic Surface Defect Detection Using Deep Learning with Channel Shuffling 19 Jun 2024 · 0 repositories · arXiv:2406.14582
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Rethinking Information Loss in Medical Image Segmentation with Various-sized Targets 28 Mar 2024 · 0 repositories · arXiv:2403.19177
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Fragility, Robustness and Antifragility in Deep Learning 15 Dec 2023 · 0 repositories · arXiv:2312.09821
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Generalizability of CNN Architectures for Face Morph Presentation Attack 17 Oct 2023 · 0 repositories · arXiv:2310.11105
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A Non-monotonic Smooth Activation Function 16 Oct 2023 · 0 repositories · arXiv:2310.10126
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Plug n' Play: Channel Shuffle Module for Enhancing Tiny Vision Transformers 9 Oct 2023 · 0 repositories · arXiv:2310.05642
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Multi-Transfer Learning Techniques for Detecting Auditory Brainstem Response 29 Aug 2023 · 0 repositories · arXiv:2308.16203
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RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection 31 Jul 2023 · 1 repository · arXiv:2307.16412Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
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JetSeg: Efficient Real-Time Semantic Segmentation Model for Low-Power GPU-Embedded Systems 19 May 2023 · 1 repository · arXiv:2305.11419
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PSDNet: Determination of Particle Size Distributions Using Synthetic Soil Images and Convolutional Neural Networks 7 Mar 2023 · 0 repositories · arXiv:2303.04269
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Use Cases for Time-Frequency Image Representations and Deep Learning Techniques for Improved Signal Classification 22 Feb 2023 · 0 repositories · arXiv:2302.11093
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QLABGrad: a Hyperparameter-Free and Convergence-Guaranteed Scheme for Deep Learning 1 Feb 2023 · 0 repositories · arXiv:2302.00252
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Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E-stained images: Achieving SOTA predictive performance with fewer data using Swin Transformer 22 Aug 2022 · 0 repositories · arXiv:2208.10495
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MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing 12 Jul 2022 · 0 repositories · arXiv:2207.05621
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Real Time Egocentric Segmentation for Video-self Avatar in Mixed Reality 4 Jul 2022 · 0 repositories · arXiv:2207.01296
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Design and Analysis of Novel Bit-flip Attacks and Defense Strategies for DNNs 24 Jun 2022 · 1 repository
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Structured Pruning is All You Need for Pruning CNNs at Initialization 4 Mar 2022 · 0 repositories · arXiv:2203.02549
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Multimodal registration of FISH and nanoSIMS images using convolutional neural network models 14 Jan 2022 · 0 repositories · arXiv:2201.05545
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ThreshNet: An Efficient DenseNet Using Threshold Mechanism to Reduce Connections 9 Jan 2022 · 1 repository · arXiv:2201.03013
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Smooth Maximum Unit: Smooth Activation Function for Deep Networks Using Smoothing Maximum Technique 1 Jan 2022 · 0 repositories
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SMU: smooth activation function for deep networks using smoothing maximum technique 8 Nov 2021 · 6 repositories · arXiv:2111.04682
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Scaling-up Diverse Orthogonal Convolutional Networks by a Paraunitary Framework 29 Sep 2021 · 0 repositories
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SAU: Smooth activation function using convolution with approximate identities 27 Sep 2021 · 0 repositories · arXiv:2109.13210
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ErfAct and Pserf: Non-monotonic Smooth Trainable Activation Functions 9 Sep 2021 · 0 repositories · arXiv:2109.04386
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High performing ensemble of convolutional neural networks for insect pest image detection 28 Aug 2021 · 0 repositories · arXiv:2108.12539
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Towards Deep and Efficient: A Deep Siamese Self-Attention Fully Efficient Convolutional Network for Change Detection in VHR Images 18 Aug 2021 · 1 repository · arXiv:2108.08157
Tasks archive 2025-07-28
20 shown of 85 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections