21 citations · 50 across the 10 of their papers we have counts for
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Spatial-Spectral Regularized Local Scaling Cut for Dimensionality Reduction in Hyperspectral Image Classification
Ramanarayan Mohanty, S L Happy, Aurobinda Routray
Dimensionality reduction (DR) methods have attracted extensive attention to provide discriminative information and reduce the computational burden of the hyperspectral image (HSI)…
A Trace Lasso Regularized L1-norm Graph Cut for Highly Correlated Noisy Hyperspectral Image
Ramanarayan Mohanty, S L Happy, Nilesh Suthar +1
This work proposes an adaptive trace lasso regularized L1-norm based graph cut method for dimensionality reduction of Hyperspectral images, called as `Trace Lasso-L1 Graph Cut' (TL…
Graph Scaling Cut with L1-Norm for Classification of Hyperspectral Images
Ramanarayan Mohanty, S L Happy, Aurobinda Routray
In this paper, we propose an L1 normalized graph based dimensionality reduction method for Hyperspectral images, called as L1-Scaling Cut (L1-SC). The underlying idea of this metho…
An Effective Feature Selection Method Based on Pair-Wise Feature Proximity for High Dimensional Low Sample Size Data
S L Happy, Ramanarayan Mohanty, Aurobinda Routray
Feature selection has been studied widely in the literature. However, the efficacy of the selection criteria for low sample size applications is neglected in most cases. Most of th…