Výsledky vyhledávání - fully‐convolutional encoder‐decoder network

A novel deep fully convolutional encoder-decoder network and similarity analysis for English education text event clustering analysis

Autoři: Zhenping Jing

Zdroj: Computer Science and Information Systems. 21:1783-1800

Pneumothorax detection and segmentation from chest X-ray radiographs using a patch-based fully convolutional encoder-decoder network

Autoři: Jakov Ivan S. Dumbrique Reynan B. Hernandez Juan Miguel L. Cruz a další

Zdroj: Front Radiol
Frontiers in Radiology, Vol 4 (2024)

Témata: Medical physics. Medical radiology. Nuclear medicine, 03 medical and health sciences, 0302 clinical medicine, pneumothorax, lung pathology detection, R895-920, 0202 electrical engineering, electronic engineering, information engineering, deep learning, convolutional neural network, 02 engineering and technology, Radiology, automatic image segmentation, Vision Transformer

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/39722784
https://doaj.org/article/64362faa1800493fb60c9bb309090038

Optimizing the Hyperparameters of Fully Convolutional Encoder–Decoder Networks for SAR Image Segmentation

Autoři: Yuanyue Liu Jin Zhao Jianchao Fan a další

Zdroj: IEEE Geoscience and Remote Sensing Letters. 21:1-5

Underwater Acoustic Signal Noise Reduction Based on a Fully Convolutional Encoder-Decoder Neural Network

Autoři: Yongqiang Song Qian Chu Feng Liu a další

Zdroj: Journal of Ocean University of China. 22:1487-1496

Optimizing Fully Convolutional Encoder-Decoder Network for Segmentation of Diabetic Eye Disease

Autoři: Abdul Qadir Khan Guangmin Sun Yu Li a další

Zdroj: Computers, Materials & Continua. 77:2481-2504

PolSAR Image Classification Via a Novel Selective Kernel Encoder-Decoder Fully Convolutional Network

Autoři: Zheng Fang Gong Zhang Qijun Dai a další

Zdroj: 2022 14th International Conference on Signal Processing Systems (ICSPS). :513-517

A Fully Convolutional Encoder-Decoder Network for Moving Object Segmentation

Autoři: Anil Turker Ender M. Eksioglu

Zdroj: 2022 International Conference on INnovations in Intelligent SysTems and Applications (INISTA). :1-6

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Very deep fully convolutional encoder–decoder network based on wavelet transform for art image fusion in cloud computing environment

Autoři: Tong Chen Juan Yang

Zdroj: Evolving Systems. 14:281-293

Témata: 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Denoising Raman spectra using fully convolutional encoder–decoder network

Autoři: Irem Loc Ibrahim Kecoglu Mehmet Burcin Unlu a další

Zdroj: Journal of Raman Spectroscopy. 53:1445-1452

Témata: 01 natural sciences, 0105 earth and related environmental sciences

Spatio-Temporal Encoder-Decoder Fully Convolutional Network for Video-Based Dimensional Emotion Recognition

Autoři: Zhengyin Du Suowei Wu Di Huang a další

Zdroj: IEEE Transactions on Affective Computing. 12:565-578

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://ieeexplore.ieee.org/document/8827932
https://doi.org/10.1109/TAFFC.2019.2940224
https://dblp.uni-trier.de/db/journals/taffco/taffco12.html#DuW0LW21
https://ieeexplore.ieee.org/document/8827932

TISNet-Enhanced Fully Convolutional Network with Encoder-Decoder Structure for Tongue Image Segmentation in Traditional Chinese Medicine

Autoři: Xiaodong Huang Jing Zhang Hui Zhang a další

Zdroj: Comput Math Methods Med

Témata: Databases, Factual, Computational Biology, Mathematical Concepts, 02 engineering and technology, Tongue Diseases, 3. Good health, Deep Learning, Tongue, Image Interpretation, Computer-Assisted, 0202 electrical engineering, electronic engineering, information engineering, Humans, Neural Networks, Computer, Medicine, Chinese Traditional, Research Article

Přístupová URL adresa: https://downloads.hindawi.com/journals/cmmm/2020/6029258.pdf
https://pubmed.ncbi.nlm.nih.gov/32831901
http://downloads.hindawi.com/journals/cmmm/2020/6029258.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7428885/
https://www.hindawi.com/journals/cmmm/2020/6029258/
https://dblp.uni-trier.de/db/journals/cmmm/cmmm2020.html#HuangZZLZ20
https://doi.org/10.1155/2020/6029258
https://pubmed.ncbi.nlm.nih.gov/32831901/

Automatic Building Extraction From High-Resolution Aerial Imagery via Fully Convolutional Encoder-Decoder Network With Non-Local Block

Autoři: Shengsheng Wang Xiaowei Hou Xin Zhao

Zdroj: IEEE Access, Vol 8, Pp 7313-7322 (2020)

Témata: 11. Sustainability, 0202 electrical engineering, electronic engineering, information engineering, non-local method, Deep learning, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, fully convolution network, building extraction, 15. Life on land, semantic segmentation, TK1-9971

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8948470/08950134.pdf
https://doaj.org/article/a481e9b2e886482082433e197569cc5b
https://dblp.uni-trier.de/db/journals/access/access8.html#WangHZ20
https://ieeexplore.ieee.org/document/8950134/
https://jglobal.jst.go.jp/detail?JGLOBAL_ID=202002239879751140

Detection of black box signal based on encoder-decoder fully convolutional networks

Autoři: Xiang Pan Jie Zhou Huazhong Ji

Zdroj: Global Oceans 2020: Singapore – U.S. Gulf Coast. :1-4

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: http://xplorestaging.ieee.org/ielx7/9388948/9388968/09389428.pdf?arnumber=9389428
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=9389428

Hybrid Attention-Based Encoder–Decoder Fully Convolutional Network for PolSAR Image Classification

Autoři: Zheng Fang Gong Zhang Qijun Dai a další

Zdroj: Remote Sensing, Vol 15, Iss 2, p 526 (2023)

Témata: polarimetric synthetic aperture radar (PolSAR), image classification, fully convolutional neural network (FCN), self-attention, receptive field, Science

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2072-4292/15/2/526; https://doaj.org/toc/2072-4292

Přístupová URL adresa: https://doaj.org/article/31a39ca9d0114cadb544ee2121f59dfc

A Fully Convolutional Encoder–Decoder Spatial–Temporal Network for Real-Time Background Subtraction

Autoři: Mingkai Qiu Xiying Li

Zdroj: IEEE Access. 7:85949-85958

Témata: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/8600701/08753645.pdf
https://ieeexplore.ieee.org/abstract/document/8753645
https://dblp.uni-trier.de/db/journals/access/access7.html#QiuL19

LF-SegNet: A Fully Convolutional Encoder–Decoder Network for Segmenting Lung Fields from Chest Radiographs

Autoři: Sanjeev Sofat Rahul Hooda Ajay Mittal

Zdroj: Wireless Personal Communications. 101:511-529

Témata: 03 medical and health sciences, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Přístupová URL adresa: https://link.springer.com/article/10.1007/s11277-018-5702-9
https://dblp.uni-trier.de/db/journals/wpc/wpc101.html#MittalHS18
https://doi.org/10.1007/s11277-018-5702-9

Raman Signal Denoising using Fully Convolutional Encoder Decoder Network

Autoři: Irem Loc Ibrahim Kecoglu Mehmet Burcin Unlu a další

Témata: 01 natural sciences, 0104 chemical sciences

Přístupová URL adresa: https://www.biorxiv.org/content/biorxiv/early/2022/01/09/2022.01.07.475347.full.pdf

Noise Suppression of Computed Tomography (CT) Images Using Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)

Autoři: H. B. Cokrokusumo I. Hariyati L. E. Lubis a další

Zdroj: Atom Indonesia, Vol 48, Iss 3, Pp 171-178 (2022)

Témata: deep learning, encoder-decoder network, fully convolutional network, image denoising, low-dose ct, residual network, Nuclear engineering. Atomic power, TK9001-9401

Popis souboru: electronic resource

Relation: https://aij.batan.go.id/index.php/aij/article/view/1113; https://doaj.org/toc/0126-1568

Přístupová URL adresa: https://doaj.org/article/073e50b0ef8a4ba0a8510d975a209b69

Autonomous Concrete Crack Semantic Segmentation Using Deep Fully Convolutional Encoder–Decoder Network in Concrete Structures Inspection

Autoři: Rundong Pu Guoqian Ren Haijiang Li a další

Zdroj: Buildings, Vol 12, Iss 11, p 2019 (2022)

Témata: deep learning, semantic segmentation, crack pattern, bridge inspection, deep convolutional neural network (DCNN), Building construction, TH1-9745

Popis souboru: electronic resource

Relation: https://www.mdpi.com/2075-5309/12/11/2019; https://doaj.org/toc/2075-5309

Přístupová URL adresa: https://doaj.org/article/ce64d81d7ce54f5488789d5496bd6f2d

A Novel Spatio-Temporal 3D Convolutional Encoder-Decoder Network for Dynamic Saliency Prediction

Autoři: Hao Li Fei Qi Guangming Shi

Zdroj: IEEE Access, Vol 9, Pp 36328-36341 (2021)

Témata: spatio-temporal features, 0202 electrical engineering, electronic engineering, information engineering, 3D fully convolutional networks, Electrical engineering. Electronics. Nuclear engineering, 02 engineering and technology, dynamic saliency prediction, Visual attention, TK1-9971

Přístupová URL adresa: https://ieeexplore.ieee.org/ielx7/6287639/9312710/09367171.pdf
https://doaj.org/article/52e6f3e821814147ba648b01530a6b21
https://ieeexplore.ieee.org/document/9367171
https://dblp.uni-trier.de/db/journals/access/access9.html#LiQS21
https://doi.org/10.1109/ACCESS.2021.3063372