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   Articles with "channel pruning" as a keyword



A Channel Pruning Algorithm Based on Depth-Wise Separable Convolution Unit

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recommendations! Published in 2019 at "IEEE Access"

DOI: 10.1109/access.2019.2956976

Abstract: Deep learning has made significant progress in many fields such as image identification, speech recognition and natural language processing, especially in the field of computer vision. The better performance of the neural network often built… read more here.

Keywords: channel pruning; separable convolution; pruning algorithm; depth wise ... See more keywords

A Channel Pruning Optimization With Layer-Wise Sensitivity in a Single-Shot Manner Under Computational Constraints

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recommendations! Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2022.3232566

Abstract: In the constrained computing environments such as mobile device or satellite on-board system, various computational factors of hardware resource can restrict the processing of deep learning (DL) services. Recent DL models such as satellite image… read more here.

Keywords: layer wise; layer; channel pruning; shot manner ... See more keywords

Acceleration-Aware Fine-Grained Channel Pruning for Deep Neural Networks via Residual Gating

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recommendations! Published in 2022 at "IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"

DOI: 10.1109/tcad.2021.3093835

Abstract: Deep neural networks have achieved remarkable advancement in various intelligence tasks. However, the massive computation and storage consumption limit applications on resource-constrained devices. While channel pruning has been widely applied to compress models, it is… read more here.

Keywords: neural networks; grained channel; acceleration; deep neural ... See more keywords

Deep Neural Network Acceleration Based on Low-Rank Approximated Channel Pruning

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recommendations! Published in 2020 at "IEEE Transactions on Circuits and Systems I: Regular Papers"

DOI: 10.1109/tcsi.2019.2958937

Abstract: Acceleration and compression on deep Convolutional Neural Networks (CNNs) have become a critical problem to develop intelligence on resource-constrained devices. Previous channel pruning can be easily deployed and accelerated without specialized hardware and software. However,… read more here.

Keywords: channel pruning; low rank; rank approximated; network ... See more keywords

An Automatically Layer-Wise Searching Strategy for Channel Pruning Based on Task-Driven Sparsity Optimization

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recommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2022.3156588

Abstract: Deep convolutional neural networks (CNNs) have achieved tremendous successes but tend to suffer from high computation costs mainly due to heavy over-parameterization, resulting in the difficulty of directly applying them to the ever-growing application demands… read more here.

Keywords: layer wise; sparsity; task; channel pruning ... See more keywords

Global Channel Pruning With Self-Supervised Mask Learning

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recommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2024.3488098

Abstract: Network pruning is widely used in model compression due to its simplicity and efficiency. Existing methods typically introduce sparse loss regularization to learn masks. However, this sparse regularization approach lacks a clear criterion for evaluating… read more here.

Keywords: supervised mask; self supervised; channel pruning; global channel ... See more keywords

Learning Low Resource Consumption CNN through Pruning and Quantization

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recommendations! Published in 2021 at "IEEE Transactions on Emerging Topics in Computing"

DOI: 10.1109/tetc.2021.3050770

Abstract: Deep learning models have evolved into powerful tools that can be used for many artificial intelligence tasks. However, deploying deep neural networks into real-world applications is still challenging due to their high computational complexity and… read more here.

Keywords: channel pruning; learning low; quantization; resource consumption ... See more keywords
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Model Compression Based on Differentiable Network Channel Pruning.

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recommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"

DOI: 10.1109/tnnls.2022.3165123

Abstract: Although neural networks have achieved great success in various fields, applications on mobile devices are limited by the computational and storage costs required for large models. The model compression (neural network pruning) technology can significantly… read more here.

Keywords: channel pruning; network channel; differentiable network; model compression ... See more keywords

IRPruneDeXt: Efficient Infrared Small Target Detection via Musical Wavelet-Regularized Channel Pruning

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recommendations! Published in 2025 at "IEEE Transactions on Neural Networks and Learning Systems"

DOI: 10.1109/tnnls.2025.3594958

Abstract: Infrared small target detection (IRSTD) refers to detecting faint targets in infrared (IR) images, which has achieved notable progress with the advent of deep learning. However, the drive for improved detection accuracy has led to… read more here.

Keywords: detection; small target; channel pruning; wavelet ... See more keywords
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Efficient Lightweight Image Classification via Coordinate Attention and Channel Pruning for Resource-Constrained Systems

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recommendations! Published in 2025 at "Future Internet"

DOI: 10.3390/fi17110489

Abstract: Image classification is central to computer vision, supporting applications from autonomous driving to medical imaging, yet state-of-the-art convolutional neural networks remain constrained by heavy floating-point operations (FLOPs) and parameter counts on edge devices. To address… read more here.

Keywords: image classification; coordinate attention; attention; channel pruning ... See more keywords

Performance-aware Approximation of Global Channel Pruning for Multitask CNNs

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recommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"

DOI: 10.48550/arxiv.2303.11923

Abstract: Global channel pruning (GCP) aims to remove a subset of channels (filters) across different layers from a deep model without hurting the performance. Previous works focus on either single task model pruning or simply adapting… read more here.

Keywords: performance aware; global channel; task; channel pruning ... See more keywords