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1
Spatial and Temporal Human Settlement Growth Differentiation with Symbolic Machine Learning for Verifying Spatial Policy Targets: Assiut Governorate, Egypt as a Case Study
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Spatial and Temporal Human Settlement Growth Differentiation with Symbolic Machine Learning for Verifying Spatial Policy Targets: Assiut Governorate, Egypt as a Case Study

Remote sensing (Basel, Switzerland), 2020-11, Vol.12 (22), p.3799 [Peer Reviewed Journal]

2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12223799

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2
Spectral-Spatial Classification of Hyperspectral Images: Three Tricks and a New Learning Setting
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Spectral-Spatial Classification of Hyperspectral Images: Three Tricks and a New Learning Setting

Remote sensing (Basel, Switzerland), 2018-07, Vol.10 (7), p.1156 [Peer Reviewed Journal]

2018. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs10071156

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3
Genus-Level Mapping of Invasive Floating Aquatic Vegetation Using Sentinel-2 Satellite Remote Sensing
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Genus-Level Mapping of Invasive Floating Aquatic Vegetation Using Sentinel-2 Satellite Remote Sensing

Remote sensing (Basel, Switzerland), 2022-07, Vol.14 (13), p.3013 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs14133013

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4
Multi-Source Data Fusion Based on Ensemble Learning for Rapid Building Damage Mapping during the 2018 Sulawesi Earthquake and Tsunami in Palu, Indonesia
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Multi-Source Data Fusion Based on Ensemble Learning for Rapid Building Damage Mapping during the 2018 Sulawesi Earthquake and Tsunami in Palu, Indonesia

Remote sensing (Basel, Switzerland), 2019-04, Vol.11 (7), p.886 [Peer Reviewed Journal]

2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs11070886

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5
Comparison of Random Forest and Support Vector Machine Classifiers for Regional Land Cover Mapping Using Coarse Resolution FY-3C Images
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Comparison of Random Forest and Support Vector Machine Classifiers for Regional Land Cover Mapping Using Coarse Resolution FY-3C Images

Remote sensing (Basel, Switzerland), 2022-02, Vol.14 (3), p.574 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs14030574

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6
Introducing ARTMO’s Machine-Learning Classification Algorithms Toolbox: Application to Plant-Type Detection in a Semi-Steppe Iranian Landscape
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Introducing ARTMO’s Machine-Learning Classification Algorithms Toolbox: Application to Plant-Type Detection in a Semi-Steppe Iranian Landscape

Remote sensing (Basel, Switzerland), 2022-09, Vol.14 (18), p.4452-4452 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs14184452

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7
A Cloud-Based Multi-Temporal Ensemble Classifier to Map Smallholder Farming Systems
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A Cloud-Based Multi-Temporal Ensemble Classifier to Map Smallholder Farming Systems

Remote sensing (Basel, Switzerland), 2018-05, Vol.10 (5), p.729 [Peer Reviewed Journal]

Copyright MDPI AG 2018 ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs10050729

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8
Spatial Prior Fuzziness Pool-Based Interactive Classification of Hyperspectral Images
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Spatial Prior Fuzziness Pool-Based Interactive Classification of Hyperspectral Images

Remote sensing (Basel, Switzerland), 2019-05, Vol.11 (9), p.1136 [Peer Reviewed Journal]

2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs11091136

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9
Robust Classification Technique for Hyperspectral Images Based on 3D-Discrete Wavelet Transform
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Robust Classification Technique for Hyperspectral Images Based on 3D-Discrete Wavelet Transform

Remote sensing (Basel, Switzerland), 2021-04, Vol.13 (7), p.1255 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs13071255

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10
Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series
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Land Cover Mapping of a Tropical Region by Integrating Multi-Year Data into an Annual Time Series

Remote sensing (Basel, Switzerland), 2015-12, Vol.7 (12), p.16274-16292 [Peer Reviewed Journal]

ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs71215833

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11
Using Voting-Based Ensemble Classifiers to Map Invasive Phragmites australis
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Using Voting-Based Ensemble Classifiers to Map Invasive Phragmites australis

Remote sensing (Basel, Switzerland), 2023-07, Vol.15 (14), p.3511 [Peer Reviewed Journal]

2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs15143511

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12
Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields
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Decision Fusion Framework for Hyperspectral Image Classification Based on Markov and Conditional Random Fields

Remote sensing (Basel, Switzerland), 2021-03, Vol.11 (6), p.624 [Peer Reviewed Journal]

2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs11060624

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13
Hybrid Computational Intelligence Models for Improvement Gully Erosion Assessment
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Hybrid Computational Intelligence Models for Improvement Gully Erosion Assessment

Remote sensing (Basel, Switzerland), 2020-01, Vol.12 (1), p.140 [Peer Reviewed Journal]

2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12010140

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14
Tree Species Classification Using Hyperspectral Imagery: A Comparison of Two Classifiers
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Tree Species Classification Using Hyperspectral Imagery: A Comparison of Two Classifiers

Remote sensing (Basel, Switzerland), 2016, Vol.8 (6), p.445-445 [Peer Reviewed Journal]

ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs8060445

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15
Comparing Thresholding with Machine Learning Classifiers for Mapping Complex Water
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Comparing Thresholding with Machine Learning Classifiers for Mapping Complex Water

Remote sensing (Basel, Switzerland), 2019-06, Vol.11 (11), p.1351 [Peer Reviewed Journal]

2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs11111351

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16
Operational Automatic Remote Sensing Image Understanding Systems: Beyond Geographic Object-Based and Object-Oriented Image Analysis (GEOBIA/GEOOIA). Part 1: Introduction
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Operational Automatic Remote Sensing Image Understanding Systems: Beyond Geographic Object-Based and Object-Oriented Image Analysis (GEOBIA/GEOOIA). Part 1: Introduction

Remote sensing (Basel, Switzerland), 2012-09, Vol.4 (9), p.2694-2735 [Peer Reviewed Journal]

Copyright MDPI AG 2012 ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs4092694

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17
Matlab Software for Supervised Habitat Mapping of Freshwater Systems Using Image Processing
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Matlab Software for Supervised Habitat Mapping of Freshwater Systems Using Image Processing

Remote sensing (Basel, Switzerland), 2021-12, Vol.13 (23), p.4906 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs13234906

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18
Tracking Land Use/Land Cover Dynamics in Cloud Prone Areas Using Moderate Resolution Satellite Data: A Case Study in Central Africa
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Tracking Land Use/Land Cover Dynamics in Cloud Prone Areas Using Moderate Resolution Satellite Data: A Case Study in Central Africa

Remote sensing (Basel, Switzerland), 2015, Vol.7 (6), p.6683-6709 [Peer Reviewed Journal]

Copyright MDPI AG 2015 ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs70606683

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19
An Operational Framework for Mapping Irrigated Areas at Plot Scale Using Sentinel-1 and Sentinel-2 Data
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An Operational Framework for Mapping Irrigated Areas at Plot Scale Using Sentinel-1 and Sentinel-2 Data

Remote sensing (Basel, Switzerland), 2021-07, Vol.13 (13), p.2584 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Attribution ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs13132584

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20
Domain Adversarial Neural Networks for Large-Scale Land Cover Classification
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Domain Adversarial Neural Networks for Large-Scale Land Cover Classification

Remote sensing (Basel, Switzerland), 2019-05, Vol.11 (10), p.1153 [Peer Reviewed Journal]

2019. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs11101153

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