Search Results - "Depthwise convolution"

DO-Conv: Depthwise Over-Parameterized Convolutional Layer by Cao, Jinming, Li, Yangyan, Sun, Mingchao, Chen, Ying, Lischinski, Dani, Cohen-Or, Daniel, Chen, Baoquan, Tu, Changhe

“…Convolutional layers are the core building blocks of Convolutional Neural Networks (CNNs). In this paper, we propose to augment a convolutional layer with an…”
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EMCAD: Efficient Multi-Scale Convolutional Attention Decoding for Medical Image Segmentation by Rahman, Md Mostafijur, Munir, Mustafa, Marculescu, Radu

“…An efficient and effective decoding mechanism is crucial in medical image segmentation, especially in scenarios with limited computational resources. However,…”
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Transformer-based network with temporal depthwise convolutions for sEMG recognition by Wang, Zefeng, Yao, Junfeng, Xu, Meiyan, Jiang, Min, Su, Jinsong

“…Considerable progress has been made in pattern recognition of surface electromyography (sEMG) with deep learning, bringing improvements to sEMG-based gesture…”
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Plant Disease Identification Using a Novel Convolutional Neural Network by Hassan, Sk Mahmudul, Maji, Arnab Kumar

“…The timely identification of plant diseases prevents the negative impact on crops. Convolutional neural network, particularly deep learning is used widely in…”
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Multiscale Residual Network With Mixed Depthwise Convolution for Hyperspectral Image Classification by Gao, Hongmin, Yang, Yao, Li, Chenming, Gao, Lianru, Zhang, Bing

“…Convolutional neural networks (CNNs) are becoming increasingly popular in modern remote sensing image processing tasks and exhibit outstanding capability for…”
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FBMSNet: A Filter-Bank Multi-Scale Convolutional Neural Network for EEG-Based Motor Imagery Decoding by Liu, Ke, Yang, Mingzhao, Yu, Zhuliang, Wang, Guoyin, Wu, Wei

“…Object: Motor imagery (MI) is a mental process widely utilized as the experimental paradigm for brain-computer interfaces (BCIs) across a broad range of basic…”
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LiteDepthwiseNet: A Lightweight Network for Hyperspectral Image Classification by Cui, Benlei, Dong, Xue-Mei, Zhan, Qiaoqiao, Peng, Jiangtao, Sun, Weiwei

“…Deep learning methods have shown considerable potential for hyperspectral image (HSI) classification, which can achieve high accuracy compared with traditional…”
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Online chatter detection via lightweight deep learning framework with efficient signal pre-processing by Zhou, Hexiang, Li, Zhoulong, Pan, Liyuan, Tian, Jinjia, Zhu, Limin

“…Deep learning methods have attracted considerable attention in the field of chatter detection due to their exceptional feature extraction and identification…”
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LungConVT-Net: A visual transformer network with blended features for Pneumonia detection by Lasker, Asifuzzaman, Ghosh, Mridul, Sk, Md Obaidullah, Goncalves, Teresa, Chakraborty, Chandan, Roy, Kaushik

“…•LungConVT-Net is designed to classify Viral Pneumonia, Bacterial Pneumonia, COVID-19, and Normal cases by considering bi-class, tri-class, and quad-class…”
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A multi-energy loads forecasting model based on dual attention mechanism and multi-scale hierarchical residual network with gated recurrent unit by Chen, Wenhao, Rong, Fei, Lin, Chuan

“…Multi-energy loads forecasting (MELF) is crucial for the effective management of integrated energy systems (IES) and the balance between energy supply and…”
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XLITE-Unet: Extremely Light and Efficient Deep learning architecture with selective atrous and axial depthwise convolution for image segmentation by Mbiethieu, Cezar, Tsopze, Norbert, Mephu-Nguifo, Engelbert

“…Semantic segmentation has achieved an exceptional success in image analysis making it easier to quickly and efficiently understand their content. Although deep…”
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Exponential linear units-guided Depthwise separable convolution network with cross attention mechanism for hyperspectral image classification by Gao, Ming, Qian, Pengjiang

“…•In this paper, a novel multi-stage convolutional neural network is proposed to maximize the extraction of HSI spatial-spectral features to improve the HSI…”
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DHEE-DETR: A dynamic hybrid and edge enhancement network for real-time vehicle detection by Wang, Ruixuan, Wu, Dinghai, Ren, Guoquan, Xia, Xu, Ren, Zhigang

“…Real-time and accurate vehicle detection is crucial in fields such as autonomous driving. Currently, mainstream DETR detectors face significant challenges in…”
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Short-term building electricity load forecasting with a hybrid deep learning method by Chen, Wenhao, Rong, Fei, Lin, Chuan

“…With the increase in energy consumption of the construction industry, building electrical load forecasting (BELF) is of crucial importance. However, there are…”
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Depthwise Separable Convolution Neural Network for High-Speed SAR Ship Detection by Zhang, Tianwen, Zhang, Xiaoling, Shi, Jun, Wei, Shunjun

“…As an active microwave imaging sensor for the high-resolution earth observation, synthetic aperture radar (SAR) has been extensively applied in military,…”
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AC-MLP: Axial Convolution-MLP Mixer for nuclei segmentation in histopathological images by Thu, Nguyen Thanh, Duong, Dinh Binh, Thao, Tran Thi, Truong, Pham Van

“…Recent MLP-Mixer has a good ability to handle long-range dependencies, however, to have a good performance, one requires huge data and expensive…”
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ULD-Net: A U-shaped branch large kernel depthwise convolution volume network for 3D medical image segmentation by Li, Weisheng, Ci, JunTong, Li, Feiyan, Zeng, Guofeng, Huang, Zhaopeng

“…Recently, the hierarchical Transformers model represented by Swin UNETR has achieved the most advanced performance in the field of 3D medical image…”
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DDF2Pol: A Dual-Domain Feature Fusion Network for PolSAR Image Classification by Alkhatib, Mohammed Q.

“…This paper presents DDF2Pol, a lightweight dual-domain convolutional neural network for PolSAR image classification. The proposed architecture integrates two…”
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Lightweight image super-resolution network based on extended convolution mixer by Gendy, Garas, Sabor, Nabil, He, Guanghui

“…The single image super-resolution (SISR) is a computer vision task needed in many real-world applications. There are many methods developed to solve ill-posed…”
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A lightweight and improved you only look once model using GhostWise convolution and attention mechanism for accurate plant disease detection by Dikici, Bunyamin, Bekciogullari, Mehmet Fatih, Acikgoz, Hakan, Ozbay, Serkan

“…Artificial intelligence enables early plant disease detection to support food security, yet achieving high accuracy with low computational cost on multi-class…”
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