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   Articles with "depthwise separable" as a keyword



A depthwise separable dense convolutional network with convolution block attention module for COVID-19 diagnosis on CT scans

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recommendations! Published in 2021 at "Computers in Biology and Medicine"

DOI: 10.1016/j.compbiomed.2021.104837

Abstract: Coronavirus disease 2019 (COVID-19) has caused more than 3 million deaths and infected more than 170 million individuals all over the world. Rapid identification of patients with COVID-19 is the key to control transmission and… read more here.

Keywords: depthwise separable; attention module; network; block attention ... See more keywords

3D Medical Image Classification with Depthwise Separable Networks

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recommendations! Published in 2019 at "Procedia Manufacturing"

DOI: 10.1016/j.promfg.2020.01.369

Abstract: Abstract This research studies a dilated depthwise separable convolution neural network (DSCN) model to identify human tissue types from 3D medical images. 3D medical image classification is a challenging task due to the unpredictable noise… read more here.

Keywords: depthwise separable; classification; image; image classification ... See more keywords

Brain Tumor Segmentation Using Partial Depthwise Separable Convolutions

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recommendations! Published in 2022 at "IEEE Access"

DOI: 10.1109/access.2022.3223654

Abstract: Gliomas are the most common and aggressive form of all brain tumors, with medial survival rates of less than two years for the highest grade. While accurate and reproducible segmentation of brain tumors is paramount… read more here.

Keywords: brain tumor; depthwise separable; tumor segmentation; brain ... See more keywords

DESEM: Depthwise Separable Convolution-Based Multimodal Deep Learning for In-Game Action Anticipation

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recommendations! Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2023.3271282

Abstract: In real-time strategy (RTS) games, to defeat their opponents, players need to choose and implement the correct sequential actions. Because RTS games like StarCraft II are real-time, players have a very limited time to choose… read more here.

Keywords: depthwise separable; game; separable convolution; convolution based ... See more keywords

DSConvNet: A Lightweight Architecture for Extracting Image Features from Depthwise Separable Convolution Network for Edge Devices

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3639410

Abstract: This paper presents DSConvNet, a novel architecture based on depthwise separable convolutional blocks for efficient multi-class image classification. Despite progress in compact convolutional neural networks (CNNs), many existing models still impose high computational costs on… read more here.

Keywords: architecture; edge; image; convolution ... See more keywords

Lightweight Gesture Recognition Based on Depthwise Separable Convolution and FECAM Attention Mechanism for sEMG

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recommendations! Published in 2025 at "IEEE Sensors Journal"

DOI: 10.1109/jsen.2025.3608298

Abstract: Surface electromyography (sEMG) is a promising approach for noninvasive gesture recognition in human–computer interaction and rehabilitation. However, existing high-accuracy models often incur high-computational costs, thereby limiting real-time deployment. To address this, we propose FSGR-Net, a… read more here.

Keywords: convolution; attention mechanism; gesture recognition; mechanism ... See more keywords

A 0.61-μW Fully Integrated Keyword-Spotting ASIC With Real-Point Serial FFT-Based MFCC and Temporal Depthwise Separable CNN

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recommendations! Published in 2024 at "IEEE Journal of Solid-State Circuits"

DOI: 10.1109/jssc.2023.3339528

Abstract: A fully integrated near-microphone keyword spotting (KWS) chip is proposed to directly interact with a passive microphone and achieve submicrowatt power for the Internet of Things (IoT) devices. First, an on-chip analog frontend (AFE) is… read more here.

Keywords: keyword spotting; depthwise; fully integrated; depthwise separable ... See more keywords

A Depthwise Separable Fully Convolutional ResNet With ConvCRF for Semisupervised Hyperspectral Image Classification

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recommendations! Published in 2021 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2021.3073661

Abstract: Hyperspectral images classification relies on the accurate and efficient extraction of discriminative features, detail preservation, and efficient learning with limited training samples. This article, therefore, presents an advanced neural network architecture combined with convolutional conditional… read more here.

Keywords: fully convolutional; separable fully; image; classification ... See more keywords

Depthwise Separable ResNet in the MAP Framework for Hyperspectral Image Classification

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recommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2020.3033149

Abstract: To build small and efficient neural networks for hyperspectral image (HSI) classification, this letter presents a depthwise separable residual neural network (ResNet). This approach, motivated by the popular MobileNet architecture, decomposes the traditional spatial-spectral convolution… read more here.

Keywords: map framework; depthwise separable; resnet; classification ... See more keywords

An FPGA-Based Energy-Efficient Reconfigurable Depthwise Separable Convolution Accelerator for Image Recognition

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recommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"

DOI: 10.1109/tcsii.2022.3180553

Abstract: With the advances in massive computing ability and big data science, deep neural network (DNN) has been developing rapidly for different applications. However, due to its extensive computation and memory usage requirements, it calls for… read more here.

Keywords: depthwise separable; energy; accelerator; energy efficient ... See more keywords

Mobile-X: Dedicated FPGA Implementation of the MobileNet Accelerator Optimizing Depthwise Separable Convolution

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recommendations! Published in 2024 at "IEEE Transactions on Circuits and Systems II: Express Briefs"

DOI: 10.1109/tcsii.2024.3440884

Abstract: MobileNet proposed depthwise separable convolution (DSC) as a replacement for standard convolution (SC), achieving significant reductions in parameters and computational complexity compared with traditional convolutional neural network (CNN) models. Recently, there has been a growing… read more here.

Keywords: accelerator; mobilenet; convolution; depthwise separable ... See more keywords