Výsledky vyhledávání - "Depthwise convolution"

WCD-YOLOv11: A lightweight YOLOv11 model for the real-time image processing in UAV

Autoři: Liangshuai Liu Lingming Meng Xiaofeng Li a další

Zdroj: Alexandria Engineering Journal, Vol 133, Iss , Pp 73-88 (2025)

Témata: Lightweight YOLO model, Real-time target detection, Drone imagery, Wavelet Transform Depthwise Convolution, Cross-Stage Partial Network (CSPNet), Partial Convolution (P-Conv), Engineering (General). Civil engineering (General), TA1-2040

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1110016825011081; https://doaj.org/toc/1110-0168

Přístupová URL adresa: https://doaj.org/article/928ad21564c74a3cbbd74c1975fba74e

A two stage deep supervised learning model with inter-layer weight sharing for multi class medical image classification

Autoři: Poonam Moral Debjani Mustafi Sudip Kumar Sahana

Zdroj: Discover Computing, Vol 28, Iss 1, Pp 1-28 (2025)

Témata: Cervical cancer, Convolutional neural network, Pap-Smear images, Inception model, Pointwise convolution, Depthwise convolution, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2948-2992

Přístupová URL adresa: https://doaj.org/article/a793c55b5f174a0fab9178642fd769b9

AC-MLP: Axial Convolution-MLP Mixer for nuclei segmentation in histopathological images

Autoři: Nguyen Thanh Thu Dinh Binh Duong Tran Thi Thao a další

Zdroj: Tạp chí Khoa học và Công nghệ, Pp 64-69 (2024)

Témata: Technology, token mixing, nuclei segmentation, depthwise convolution, mlp-mixer

Přístupová URL adresa: https://doaj.org/article/221d48bd385449efb8e9c4e7c18cdfff

Fusing Depthwise and Pointwise Convolutions for Efficient Inference on GPUs

Autoři: Mohammad Qararyah, Fareed Azhar, Muhammad Waqar Maleki, Mohammad Ali a další

Zdroj: Very Efficient Deep Learning in IOT (VEDLIoT) EPI SGA2 53rd International Conference on Parallel Processing, ICPP 2024, Gotland, Sweden ACM International Conference Proceeding Series. :58-67

Témata: layer fusion, depthwise convolution, CNN, vision transformer, pointwise convolution, GPU

Popis souboru: electronic

Přístupová URL adresa: https://research.chalmers.se/publication/542723
https://research.chalmers.se/publication/543131
https://research.chalmers.se/publication/543131/file/543131_Fulltext.pdf

nnHCCNeXt: A Lightweight Algorithm for Hepatocellular Carcinoma Segmentation in 3D Venous Phase CT Imaging

Autoři: Lin Zhu Manxia Zhou Songqing He a další

Zdroj: IEEE Access, Vol 13, Pp 185624-185636 (2025)

Témata: Hepatocellular carcinoma, venous phase CT image, 3D medical image segmentation, inception depthwise convolution, residual group attention gate, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Popis souboru: electronic resource

Relation: https://ieeexplore.ieee.org/document/11217970/; https://doaj.org/toc/2169-3536

Přístupová URL adresa: https://doaj.org/article/a7562377591746c38d2759387941d690

YOLOv11-GLIDE: An Improved YOLOv11n Student Behavior Detection Algorithm Based on Scale-Based Dynamic Loss and Channel Prior Convolutional Attention

Autoři: Haiyan Wang Guiyuan Gao Wei Zhang a další

Zdroj: Sensors, Vol 25, Iss 22, p 6972 (2025)

Témata: YOLOv11n, Scale-based Dynamic Loss, Channel Prior Convolutional Attention, Sparse Depthwise Convolution, Chemical technology, TP1-1185

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1424-8220/25/22/6972; https://doaj.org/toc/1424-8220

Přístupová URL adresa: https://doaj.org/article/bb90e9c039914167b7ab648ed1c90bcf

Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Autoři: Guanghua Yi Xinhong Hao Xiaopeng Yan a další

Zdroj: Defence Technology, Vol 33, Iss, Pp 364-373 (2024)

Témata: Automatic modulation recognition, Military Science, 0202 electrical engineering, electronic engineering, information engineering, Depthwise convolution, Radiation source signals, 02 engineering and technology, Two-dimensional data matrix, Residual neural network

Přístupová URL adresa: https://doaj.org/article/1e8479ac0e9a4578a4c00fe3bdfe55a4

RMDNet-Deep Learning Paradigms for Effective Malware Detection and Classification

Autoři: S. Puneeth Shyam Lal Mahendra Pratap Singh a další

Zdroj: IEEE Access, Vol 12, Pp 82622-82635 (2024)

Témata: concatenation, cyber security, 0202 electrical engineering, electronic engineering, information engineering, convolution, deep learning, depthwise convolution, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, Binary classification, TK1-9971

Přístupová URL adresa: https://doaj.org/article/1bc53d9e17514f7a88bf5031f5dd12a2

A Hybrid Transformer-LSTM Model With 3D Separable Convolution for Video Prediction

Autoři: Mareeta Mathai Ying Liu Nam Ling

Zdroj: IEEE Access, Vol 12, Pp 39589-39602 (2024)

Témata: self-attention, 3D separable convolution, 0209 industrial biotechnology, 0202 electrical engineering, electronic engineering, information engineering, deep learning, depthwise convolution, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, LSTM, pointwise convolution, TK1-9971

Přístupová URL adresa: https://doaj.org/article/5b081dbb36034408bb4582646b8367f2

Enhancing LiDAR-Based Object Recognition Through a Novel Denoising and Modified GDANet Framework

Autoři: Oddy Virgantara Putra Moch. Iskandar Riansyah Farah Zakiyah Rahmanti a další

Zdroj: IEEE Access, Vol 12, Pp 7285-7297 (2024)

Témata: 0209 industrial biotechnology, LiDAR, 0202 electrical engineering, electronic engineering, information engineering, Depthwise convolution, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, point cloud denoising, human pose classification, object recognition, TK1-9971

Přístupová URL adresa: https://doaj.org/article/5860008870234540b1bba1209bd52066

In-Wheel Motor Fault Diagnosis Method Based on Two-Stream 2DCNNs with DCBA Module

Autoři: Junwei Zhu Xupeng Ouyang Zongkang Jiang a další

Zdroj: Sensors, Vol 25, Iss 15, p 4617 (2025)

Témata: in-wheel motor, fault diagnosis, two-stream 2DCNNs, depthwise convolution block attention, Chemical technology, TP1-1185

Popis souboru: electronic resource

Relation: https://www.mdpi.com/1424-8220/25/15/4617; https://doaj.org/toc/1424-8220

Přístupová URL adresa: https://doaj.org/article/78ea00af09c34d90a32f854505eb3d97

Epilepsy Diagnosis from EEG Signals Using Continuous Wavelet Transform-Based Depthwise Convolutional Neural Network Model

Autoři: Fırat Dişli Mehmet Gedikpınar Hüseyin Fırat a další

Zdroj: Diagnostics ; Volume 15 ; Issue 1 ; Pages: 84

Témata: epilepsy, depthwise convolution, image concatenate, continuous wavelet transform

Popis souboru: application/pdf

Relation: Machine Learning and Artificial Intelligence in Diagnostics; https://dx.doi.org/10.3390/diagnostics15010084

Dostupnost: https://doi.org/10.3390/diagnostics15010084

Plant Disease Identification Using a Novel Convolutional Neural Network

Autoři: Sk Mahmudul Hassan Arnab Kumar Maji

Zdroj: IEEE Access, Vol 10, Pp 5390-5401 (2022)

Témata: machine learning, 0202 electrical engineering, electronic engineering, information engineering, deep learning, 0401 agriculture, forestry, and fisheries, depthwise convolution, Electrical engineering. Electronics. Nuclear engineering, 04 agricultural and veterinary sciences, 02 engineering and technology, Plant disease, pointwise convolution, TK1-9971

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/9668973/09674894.pdf
https://doaj.org/article/ef5f5ff9416b43ae89d05b79d5fb5407

A Fast Lightweight 3D Separable Convolutional Neural Network With Multi-Input Multi-Output for Moving Object Detection

Autoři: Bingxin Hou Ying Liu Nam Ling a další

Zdroj: IEEE Access, Vol 9, Pp 148433-148448 (2021)

Témata: scene independent evaluation, multi-input multi-output, 0202 electrical engineering, electronic engineering, information engineering, Convolutional neural network, moving object detection, depthwise convolution, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, pointwise convolution, TK1-9971

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/6514899/09592757.pdf
https://doaj.org/article/95b6bf8fc40a4a729d71a7693329d1e2
https://dblp.uni-trier.de/db/journals/access/access9.html#HouLLLR21

Feature Recalibration in Deep Learning via Depthwise Squeeze and Refinement Operations

Autoři: Xingpeng Zhang Xiaohong Zhang

Zdroj: IEEE Access, Vol 8, Pp 79046-79055 (2020)

Témata: Feature recalibration, 03 medical and health sciences, 0302 clinical medicine, global information, 0202 electrical engineering, electronic engineering, information engineering, depthwise convolution, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, squeeze, TK1-9971

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8948470/09079495.pdf
https://doaj.org/article/c5022382f6094330848e5a48501d48fb
https://dblp.uni-trier.de/db/journals/access/access8.html#ZhangZ20d
https://ieeexplore.ieee.org/document/9079495/

Learning to Recognize Chest-Xray Images Faster and More Efficiently Based on Multi-Kernel Depthwise Convolution

Autoři: Mengjie Hu Hezheng Lin Zimeng Fan a další

Zdroj: IEEE Access, Vol 8, Pp 37265-37274 (2020)

Témata: Chest x-ray recognition, 03 medical and health sciences, 0302 clinical medicine, multi-kernels depthwise convolution, 0202 electrical engineering, electronic engineering, information engineering, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, lightweight networks, TK1-9971, 3. Good health

Přístupová URL adresa: https://doaj.org/article/cd6fc7ae90364a4aae9b0eb16623203e
https://dblp.uni-trier.de/db/journals/access/access8.html#HuLFGYLS20
https://doi.org/10.1109/ACCESS.2020.2974242
https://doaj.org/article/cd6fc7ae90364a4aae9b0eb16623203e
https://ieeexplore.ieee.org/document/9000602

EADD-YOLO: An efficient and accurate disease detector for apple leaf using improved lightweight YOLOv5

Autoři: Shisong Zhu Wanli Ma Jianlong Wang a další

Zdroj: Front Plant Sci
Frontiers in Plant Science, Vol 14 (2023)

Témata: SIoU loss, 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, Plant culture, disease detection, depthwise convolution, Plant Science, 02 engineering and technology, coordinate attention, apple leaf, SB1-1110

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/36909428
https://doaj.org/article/a94eab0c585a421f85fb1693edd79c9e

A Machine Learning Approach for the Estimation of Severity of Psoriasis Disorder Using Depth-Wise Convolution Neural Network

Autoři: T R Arunkumar H S Jayanna

Témata: Psoriasis, Depthwise convolution neural network, Machine Learning, Keras, Skin Texture

Relation: https://zenodo.org/records/12732095; oai:zenodo.org:12732095; https://doi.org/10.17485/IJST/v16i5.1723

Dostupnost: https://doi.org/10.17485/IJST/v16i5.1723
https://zenodo.org/records/12732095
https://indjst.org/articles/a-machine-learning-approach-for-the-estimation-of-severity-of-psoriasis-disorder-using-depth-wise-convolution-neural-network

Shot Boundary Detection with 3D Depthwise Convolutions and Visual Attention

Autoři: Esteve Brotons, Miguel José Lucendo, Francisco Javier Rodríguez Juan, Javier a další

Přispěvatelé: Esteve Brotons, Miguel José Lucendo, Francisco Javier Rodríguez Juan, Javier a další

Témata: Shot boundary detection, 3D convolution, Depthwise convolution, Visual attention

Relation: https://doi.org/10.3390/s23167022; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/TED2021-130890B-C21; info:eu-repo/grantAgreement/EC/HE/101086387; http://hdl.handle.net/10045/136718

Dostupnost: http://hdl.handle.net/10045/136718
https://doi.org/10.3390/s23167022

MCPT: Mixed Convolutional Parallel Transformer for Polarimetric SAR Image Classification

Autoři: Wenke Wang Jianlong Wang Bibo Lu a další

Zdroj: Remote Sensing, Vol 15, Iss 11, p 2936 (2023)

Témata: polarimetric SAR, convolutional neural network, vision transformer, mixed depthwise convolution tokenization, parallel encoder, global average pooling, Science

Relation: https://www.mdpi.com/2072-4292/15/11/2936; https://doaj.org/toc/2072-4292; https://doaj.org/article/1d3f011a206e47dd9deda43a270647b0

Dostupnost: https://doi.org/10.3390/rs15112936
https://doaj.org/article/1d3f011a206e47dd9deda43a270647b0