Classification of imbalanced hyperspectral images using SMOTE-based deep learning methods
Author:
Publisher
Elsevier BV
Subject
Artificial Intelligence,Computer Science Applications,General Engineering
Reference28 articles.
1. Nieves, Juan. (2020). Hyperspectral imaging. 10.1007/978-3-642-27851-8_425-1.
2. Paoletti, Mercedes, Haut, Juan, Pereira, Nuno, Plaza, Javier, & Plaza, Antonio. (2021). Ghostnet for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing 1–16. 10.1109/TGRS.2021.3050257.
3. Sarker, Yeahia, Fahim, Shahriar Rahman, Hosen, Md. Sakhawat, Sarker, Subrata, Mondal, Md, Das, Sajal. (2020). Regularized singular value decomposition based multidimensional convolutional neural network for hyperspectral image classification. 10.1109/TENSYMP50017.2020.9230701.
4. Deep learning classifiers for hyperspectral imaging: A review;Paoletti;ISPRS Journal of Photogrammetry and Remote Sensing,2019
5. Khan, Uzair, Sidike, Paheding, Elkin, Colin, & Devabhaktuni, Vijay. (2020). Trends in deep learning for medical hyperspectral image analysis.
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