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Pedram Ghamisi
Pedram Ghamisi
HZDR & Lancaster University, Group Leader and Professor
Email confirmado em hzdr.de - Página inicial
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Deep feature extraction and classification of hyperspectral images based on convolutional neural networks
Y Chen, H Jiang, C Li, X Jia, P Ghamisi
IEEE transactions on geoscience and remote sensing 54 (10), 6232-6251, 2016
28502016
Deep learning for hyperspectral image classification: An overview
S Li, W Song, L Fang, Y Chen, P Ghamisi, JA Benediktsson
IEEE Transactions on Geoscience and Remote Sensing 57 (9), 6690-6709, 2019
15652019
Deep recurrent neural networks for hyperspectral image classification
L Mou, P Ghamisi, XX Zhu
IEEE transactions on geoscience and remote sensing 55 (7), 3639-3655, 2017
13782017
Support vector machine versus random forest for remote sensing image classification: A meta-analysis and systematic review
M Sheykhmousa, M Mahdianpari, H Ghanbari, F Mohammadimanesh, ...
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2020
8212020
Advances in hyperspectral image and signal processing: A comprehensive overview of the state of the art
P Ghamisi, N Yokoya, J Li, W Liao, S Liu, J Plaza, B Rasti, A Plaza
IEEE Geoscience and Remote Sensing Magazine 5 (4), 37-78, 2017
7752017
Generative adversarial networks for hyperspectral image classification
L Zhu, Y Chen, P Ghamisi, JA Benediktsson
IEEE Transactions on Geoscience and Remote Sensing 56 (9), 5046-5063, 2018
7002018
Advanced Supervised Spectral Classifiers for Hyperspectral Images: A Review
P Ghamisi, J Plaza, Y Chen, J Li, A Plaza
IEEE Geoscience and Remote Sensing Magazine (GRSM), 2017
692*2017
Covid-19 outbreak prediction with machine learning
SF Ardabili, A Mosavi, P Ghamisi, F Ferdinand, AR Varkonyi-Koczy, ...
Algorithms 13 (10), 249, 2020
5612020
Feature selection based on hybridization of genetic algorithm and particle swarm optimization
P Ghamisi, JA Benediktsson
IEEE Geoscience and Remote Sensing Letters 12 (2), 309-313, 2015
5262015
Feature extraction for hyperspectral imagery: The evolution from shallow to deep: Overview and toolbox
B Rasti, D Hong, R Hang, P Ghamisi, X Kang, J Chanussot, ...
IEEE Geoscience and Remote Sensing Magazine 8 (4), 60-88, 2020
5062020
Cascaded recurrent neural networks for hyperspectral image classification
R Hang, Q Liu, D Hong, P Ghamisi
IEEE Transactions on Geoscience and Remote Sensing 57 (8), 5384-5394, 2019
4942019
Multisource and multitemporal data fusion in remote sensing: A comprehensive review of the state of the art
P Ghamisi, B Rasti, N Yokoya, Q Wang, B Hofle, L Bruzzone, F Bovolo, ...
IEEE Geoscience and Remote Sensing Magazine 7 (1), 6-39, 2019
4652019
A survey on spectral–spatial classification techniques based on attribute profiles
P Ghamisi, M Dalla Mura, JA Benediktsson
IEEE Transactions on Geoscience and Remote Sensing 53 (5), 2335-2353, 2015
3912015
COVID-19 pandemic prediction for Hungary; a hybrid machine learning approach
G Pinter, I Felde, A Mosavi, P Ghamisi, R Gloaguen
Mathematics 8 (6), 890, 2020
3702020
SpectralGPT: Spectral remote sensing foundation model
D Hong, B Zhang, X Li, Y Li, C Li, J Yao, N Yokoya, H Li, P Ghamisi, X Jia, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024
3672024
An efficient method for segmentation of images based on fractional calculus and natural selection
P Ghamisi, MS Couceiro, JA Benediktsson, NMF Ferreira
Expert Systems with Applications 39 (16), 12407-12417, 2012
3472012
Frontiers in Spectral-Spatial Classification of Hyperspectral Images
P Ghamisi, E Maggiori, S Li, R Souza, Y Tarabalka, G Moser, AD Giorgi, ...
IEEE Geoscience and Remote Sensing Magazine, 2018
340*2018
Multilevel image segmentation based on fractional-order Darwinian particle swarm optimization
P Ghamisi, MS Couceiro, FML Martins, JA Benediktsson
IEEE Transactions on Geoscience and Remote Sensing, 52 (5), 2382-2394, 2014
3142014
Noise reduction in hyperspectral imagery: Overview and application
B Rasti, P Scheunders, P Ghamisi, G Licciardi, J Chanussot
Remote Sensing 10 (3), 482, 2018
3062018
Unsupervised spectral–spatial feature learning via deep residual Conv–Deconv network for hyperspectral image classification
L Mou, P Ghamisi, XX Zhu
IEEE Transactions on Geoscience and Remote Sensing 56 (1), 391-406, 2017
3052017
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