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Kun Tan
Kun Tan
在 geo.ecnu.edu.cn 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Multiple classifier system for remote sensing image classification: A review
P Du, J Xia, W Zhang, K Tan, Y Liu, S Liu
Sensors 12 (4), 4764-4792, 2012
3302012
Fusion of difference images for change detection over urban areas
P Du, S Liu, P Gamba, K Tan, J Xia
IEEE journal of selected topics in applied earth observations and remote …, 2012
1812012
Estimation of the spatial distribution of heavy metal in agricultural soils using airborne hyperspectral imaging and random forest
K Tan, H Wang, L Chen, Q Du, P Du, C Pan
Journal of hazardous materials 382, 120987, 2020
1592020
Advances of four machine learning methods for spatial data handling: A review
P Du, X Bai, K Tan, Z Xue, A Samat, J Xia, E Li, H Su, W Liu
Journal of Geovisualization and Spatial Analysis 4, 1-25, 2020
1412020
Caps-TripleGAN: GAN-assisted CapsNet for hyperspectral image classification
X Wang, K Tan, Q Du, Y Chen, P Du
IEEE Transactions on Geoscience and Remote Sensing 57 (9), 7232-7245, 2019
1322019
Estimating the distribution trend of soil heavy metals in mining area from HyMap airborne hyperspectral imagery based on ensemble learning
K Tan, W Ma, L Chen, H Wang, Q Du, P Du, B Yan, R Liu, H Li
Journal of Hazardous Materials 401, 123288, 2021
1292021
Review of hyperspectral remote sensing image classification
PJ Du, JS Xia, ZH Xue, K Tan, HJ Su, R Bao
Journal of Remote Sensing 20 (2), 236-256, 2016
1172016
A novel semi-supervised hyperspectral image classification approach based on spatial neighborhood information and classifier combination
K Tan, J Hu, J Li, P Du
ISPRS journal of photogrammetry and remote sensing 105, 19-29, 2015
1052015
Hyperspectral image classification on insufficient-sample and feature learning using deep neural networks: A review
N Wambugu, Y Chen, Z Xiao, K Tan, M Wei, X Liu, J Li
International Journal of Applied Earth Observation and Geoinformation 105 …, 2021
1002021
A deep siamese network with hybrid convolutional feature extraction module for change detection based on multi-sensor remote sensing images
M Wang, K Tan, X Jia, X Wang, Y Chen
Remote Sensing 12 (2), 205, 2020
982020
Deep learning based regression for optically inactive inland water quality parameter estimation using airborne hyperspectral imagery
C Niu, K Tan, X Jia, X Wang
Environmental Pollution 286, 117534, 2021
892021
Automatic change detection in high-resolution remote sensing images by using a multiple classifier system and spectral–spatial features
K Tan, X Jin, A Plaza, X Wang, L Xiao, P Du
IEEE Journal of Selected topics in applied Earth observations and Remote …, 2016
872016
Hyperspectral image classification using band selection and morphological profiles
K Tan, E Li, Q Du, P Du
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2013
852013
An efficient semi-supervised classification approach for hyperspectral imagery
K Tan, E Li, Q Du, P Du
ISPRS Journal of Photogrammetry and Remote Sensing 97, 36-45, 2014
782014
Wavelet SVM in reproducing kernel Hilbert space for hyperspectral remote sensing image classification
P Du, K Tan, X Xing
Optics Communications 283 (24), 4978-4984, 2010
772010
Anomaly detection for hyperspectral imagery based on the regularized subspace method and collaborative representation
K Tan, Z Hou, F Wu, Q Du, Y Chen
Remote sensing 11 (11), 1318, 2019
762019
Random forest–based estimation of heavy metal concentration in agricultural soils with hyperspectral sensor data
K Tan, W Ma, F Wu, Q Du
Environmental monitoring and assessment 191, 1-14, 2019
722019
Remote sensing image interpretation for urban environment analysis: methods, system and examples
P Du, P Liu, J Xia, L Feng, S Liu, K Tan, L Cheng
Remote Sensing 6 (10), 9458-9474, 2014
712014
Object-based change detection using multiple classifiers and multi-scale uncertainty analysis
K Tan, Y Zhang, X Wang, Y Chen
Remote Sensing 11 (3), 359, 2019
702019
Evaluation of the spatio-temporal pattern of urban ecological security using remote sensing and GIS
P Du, J Xia, Q Du, Y Luo, K Tan
International journal of remote sensing 34 (3), 848-863, 2013
702013
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