A sub-pixel mapping method based on an attraction model for multiple shifted remotely sensed images

Neurocomputing ◽

10.1016/j.neucom.2012.12.078 ◽

2014 ◽

Vol 134 ◽

pp. 79-91 ◽

Author(s):

Xiong Xu ◽

Yanfei Zhong ◽

Liangpei Zhang

Keyword(s):

Remotely Sensed ◽

Mapping Method ◽

Attraction Model ◽

Remotely Sensed Images ◽

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Sub-pixel Mapping with Multiple Shifted Remotely Sensed Images Based on Attraction Model

Intelligent Science and Intelligent Data Engineering - Lecture Notes in Computer Science ◽

10.1007/978-3-642-31919-8_62 ◽

2012 ◽

pp. 482-489 ◽

Author(s):

Xiong Xu ◽

Yanfei Zhong ◽

Liangpei Zhang

Keyword(s):

Remotely Sensed ◽

Attraction Model ◽

Remotely Sensed Images ◽

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Supervised Sub-Pixel Mapping for Change Detection from Remotely Sensed Images with Different Resolutions

Remote Sensing ◽

10.3390/rs9030284 ◽

2017 ◽

Vol 9 (3) ◽

pp. 284 ◽

Author(s):

Ke Wu ◽

Qian Du ◽

Yi Wang ◽

Yetao Yang

Keyword(s):

Change Detection ◽

Remotely Sensed ◽

Remotely Sensed Images ◽

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Coarse-Grained Analysis of Crystalline Defects Caused by Ion Beam Irradiation:PM (Pixel Mapping) Method

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.129.238 ◽

2009 ◽

Vol 129 (2) ◽

pp. 238-243

Author(s):

Sachiko T.

Keyword(s):

Ion Beam ◽

Mapping Method ◽

Coarse Grained ◽

Crystalline Defects ◽

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A Siamese convolutional neural network with high–low level feature fusion for change detection in remotely sensed images

Remote Sensing Letters ◽

10.1080/2150704x.2021.1892851 ◽

2021 ◽

Vol 12 (4) ◽

pp. 387-396

Author(s):

Hao Zhou ◽

Mi Zhang ◽

Xiangyun Hu ◽

Kun Li ◽

Jing Sun

Keyword(s):

Neural Network ◽

Change Detection ◽

Convolutional Neural Network ◽

Feature Fusion ◽

Remotely Sensed ◽

Low Level ◽

Remotely Sensed Images

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MACU-Net for Semantic Segmentation of Fine-Resolution Remotely Sensed Images

IEEE Geoscience and Remote Sensing Letters ◽

10.1109/lgrs.2021.3052886 ◽

2021 ◽

pp. 1-5

Author(s):

Rui Li ◽

Chenxi Duan ◽

Shunyi Zheng ◽

Ce Zhang ◽

Peter M. Atkinson

Keyword(s):

Semantic Segmentation ◽

Remotely Sensed ◽

Remotely Sensed Images ◽

Fine Resolution

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A Phenology-Based Cropping Pattern (PBCP) Mapping Method Based on Remotely Sensed Time-Series Vegetation Index Data

2019 8th International Conference on Agro-Geoinformatics (Agro-Geoinformatics) ◽

10.1109/agro-geoinformatics.2019.8820717 ◽

2019 ◽

Author(s):

Jianhong Liu

Keyword(s):

Time Series ◽

Vegetation Index ◽

Remotely Sensed ◽

Mapping Method ◽

Cropping Pattern ◽

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Super-resolution target identification from remotely sensed images using a Hopfield neural network

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/36.917895 ◽

2001 ◽

Vol 39 (4) ◽

pp. 781-796 ◽

Author(s):

A.J. Tatem ◽

H.G. Lewis ◽

P.M. Atkinson ◽

M.S. Nixon

Keyword(s):

Neural Network ◽

Target Identification ◽

Super Resolution ◽

Hopfield Neural Network ◽

Remotely Sensed ◽

Remotely Sensed Images

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A Model-Based Approach to Multiresolution Fusion in Remotely Sensed Images

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2006.873340 ◽

2006 ◽

Vol 44 (9) ◽

pp. 2549-2562 ◽

Author(s):

M.V. Joshi ◽

L. Bruzzone ◽

S. Chaudhuri

Keyword(s):

Remotely Sensed ◽

Model Based ◽

Remotely Sensed Images

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An ensemble approach for the detection and classification of mixed pixels of remotely sensed images

2018 4th International Conference on Recent Advances in Information Technology (RAIT) ◽

10.1109/rait.2018.8389026 ◽

2018 ◽

Author(s):

Shabnam Choudhury ◽

Anik Chaudhuri ◽

Dipti Patra

Keyword(s):

Remotely Sensed ◽

Ensemble Approach ◽

Mixed Pixels ◽

Remotely Sensed Images

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Cloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model

ISPRS Journal of Photogrammetry and Remote Sensing ◽

10.1016/j.isprsjprs.2014.02.015 ◽

2014 ◽

Vol 92 ◽

pp. 54-68 ◽

Author(s):

Qing Cheng ◽

Huanfeng Shen ◽

Liangpei Zhang ◽

Qiangqiang Yuan ◽

Chao Zeng

Keyword(s):

Remotely Sensed ◽

Remotely Sensed Images ◽

Spatio Temporal ◽

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