In this paper, we propose to improve the classification accuracy of hyperspectral images by fusing the capabilities of the support vector machine (SVM) ...
May 30, 2016 · In this paper, we propose to improve the classification accuracy of hyperspectral images by fusing the capabilities of the support vector ...
Robust classification of hyperspectral images based on the combination ...
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Abstract –In this paper, we propose to improve the classification accuracy of hyperspectral images by fusing the capabilities of the support vector machine ...
Robust classification of hyperspectral images based on the combination of supervised and unsupervised learning paradigms · A novel method for minimizing data ...
In this paper, we introduce a novel framework for improved classification of hyperspectral images based on the combination of supervised and unsupervised ...
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In this paper, we propose to improve the classification accuracy of hyperspectral images by fusing the capabilities of the support vector machine (SVM) ...
The novelty of this work is to bring out the features of 3D-DWT applicable to hyperspectral images classification using Haar, Fejér-Korovkin and Coiflet ...
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May 14, 2024 · This survey provides a comprehensive overview of the current trends and future prospects in HSC, focusing on the advancements from DL models to the emerging ...
Jan 30, 2022 · Othman, "Robust classification of hyperspectral images based on the combination of supervised and unsupervised learning paradigms," 2012 ...
Robust classification of hyperspectral images based on the combination of supervised and unsupervised learning paradigms. N Alajlan, Y Bazi, H AlHichri, E ...