Suchergebnisse - "Attention encoder–decoder network"

Precision Meets Speed: An Attention Encoder–Decoder Network for Deforestation Segmentation

Autoren: Giovana A. Benvenuto Rogério G. Negri Marilaine Colnago et al.

Quelle: IEEE Geoscience and Remote Sensing Letters. 22:1-5

Schlagwörter: Geoinformatics, Geomatic engineering, Physical geography and environmental geoscience

MHAED-Net: a lightweight multiscale hybrid attention encoder-decoder network for the efficient segmentation of industrial forging images

Autoren: Miao Wan Y. C. Lin Shu-Xin Li et al.

Quelle: The Journal of Supercomputing. 81

A Temporal-Spatial Attention Encoder-Decoder Network for Multivariate Time Series Forecasting and Its Application in Hot Blast Stove Production

Autoren: Yinghua Yang Tingwei Qin Xiaozhi Liu

Quelle: 2024 36th Chinese Control and Decision Conference (CCDC). :984-989

Offline Signature Verification Using a 2D Attention Encoder-Decoder Network

Autoren: Zhuohui Chen Zhicong Lin Chunlian Lin et al.

Quelle: Proceedings of the 2023 12th International Conference on Networks, Communication and Computing. :274-287

EA-EDNet: encapsulated attention encoder-decoder network for 3D reconstruction in low-light-level environment

Autoren: Yulin Deng Liju Yin Xiaoning Gao et al.

Quelle: Multimedia Systems. 29:2263-2279

MGU-Net: a multiscale gate attention encoder-decoder network for medical image segmentation

Autoren: Yong Wan Tao Lei Qi Chen et al.

Quelle: International Journal of Computer Applications in Technology. 71:275-285

Attention Encoder-Decoder Network Based Autonomous Risk Driving Identification for Connected Heavy-Duty Vehicles

Autoren: Tian Xu Kun Tang Tangyi Guo

Quelle: Lecture Notes in Electrical Engineering ISBN: 9789819711024

FDAENet: frequency domain attention encoder-decoder network for road extraction of remote sensing images

Autoren: Hai Huan Bo Zhang

Quelle: Journal of Applied Remote Sensing. 18

An Attention Encoder-Decoder Network Based on Generative Adversarial Network for Remote Sensing Image Dehazing

Autoren: Liquan Zhao Yupeng Zhang Ying Cui

Quelle: IEEE Sensors Journal. 22:10890-10900

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

Recurrent attention encoder–decoder network for multi-step interval wind power prediction

Autoren: Xiaoling Ye Chengcheng Liu Xiong Xiong et al.

Quelle: Energy. 315:134317

MAU-Net: A Multiscale Attention Encoder-decoder Network for Liver and Liver-tumor Segmentation

Autoren: Le Liu Jian Su HuLin Liu et al.

Quelle: 2022 the 5th International Conference on Image and Graphics Processing (ICIGP). :202-208

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

MAENet: Multiple Attention Encoder–Decoder Network for Farmland Segmentation of Remote Sensing Images

Autoren: Hai Huan Yuan Liu Yaqin Xie et al.

Quelle: IEEE Geoscience and Remote Sensing Letters. 19:1-5

Schlagwörter: 0211 other engineering and technologies, 0207 environmental engineering, 02 engineering and technology

Context-Aware Attention Encoder-Decoder Network for Connected Heavy-Duty Vehicle Aggressive Driving Identification Under Naturalistic Driving Conditions

Autoren: Kun Tang Li Yang Yongfeng Ma et al.

Quelle: IEEE Transactions on Intelligent Transportation Systems. 25:9710-9722

CA-SegNet: A channel-attention encoder–decoder network for histopathological image segmentation

Autoren: Feng He Weibo Wang Lijuan Ren et al.

Weitere Verfasser: Feng He Weibo Wang Lijuan Ren et al.

Quelle: Biomedical Signal Processing and Control. 96:106590

Schlagwörter: Deep learning Channel attention Encoder-decoder Medical image segmentation Histopathological images, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging

基于残差注意力编-解码网络的道路提取方法.

Alternate Title: A road extraction method based on residual attention encoder-decoder network.

Autoren: 齐然然 帕力旦·吐尔逊 汤泊川 et al.

Quelle: Computer Engineering & Science / Jisuanji Gongcheng yu Kexue. Jan2025, Vol. 47 Issue 1, p119-129. 11p.

JAED-Net: joint attention encoder–decoder network for road extraction from remote sensing images

Autoren: Ranran Qi Palidan Tuerxun Yurong Qian et al.

Quelle: Journal of Applied Remote Sensing. 17

Vessel Trajectory Prediction Based on Automatic Identification System Data: Multi-Gated Attention Encoder Decoder Network

Autoren: Fan Yang Chunlin He Yi Liu et al.

Quelle: Journal of Marine Science and Engineering, Vol 12, Iss 10, p 1695 (2024)

Schlagwörter: vessel trajectory prediction, deep learning, encoder–decoder model, AIS data, Naval architecture. Shipbuilding. Marine engineering, VM1-989, Oceanography, GC1-1581

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2077-1312/12/10/1695; https://doaj.org/toc/2077-1312

Zugangs-URL: https://doaj.org/article/3b3cf22511204a46a64ff113f06104aa

A Novel Two-Factor Attention Encoder-Decoder Network through Combining Temporal and Prior Knowledge for Weather Forecasting

Autoren: Pengfei Chen Hualu Zhang Xiaozhong Ji et al.

Quelle: 2019 International Joint Conference on Neural Networks (IJCNN). :1-8

Schlagwörter: 13. Climate action, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 01 natural sciences, 0105 earth and related environmental sciences

Precision Meets Speed: An Attention Encoder-Decoder Network for Deforestation Segmentation

Autoren: Giovana A Benvenuto Rogério G Negri Marilaine Colnago et al.

Schlagwörter: Geoinformatics, Physical geography and environmental geoscience, Geomatic engineering, Geological & Geomatics Engineering, 3704 Geoinformatics, 3709 Physical geography and environmental geoscience, 4013 Geomatic engineering

Verfügbarkeit: https://doi.org/10.25455/wgtn.29631728
https://figshare.com/articles/journal_contribution/Precision_Meets_Speed_An_Attention_Encoder-Decoder_Network_for_Deforestation_Segmentation/29631728

FRANet: A Feature Refinement Attention Network for SAR Image Denoising

Autoren: Shuaiqi Liu Yu Lei Qi Hu et al.

Quelle: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 12343-12363 (2025)

Schlagwörter: Ocean engineering, image denoising, QC801-809, Attention encoder–decoder network, Geophysics. Cosmic physics, deep learning, feature refinement, synthetic aperture radar (SAR), TC1501-1800

Zugangs-URL: https://doaj.org/article/5c07b3199eac47f1bf7e16b2322f38c7