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Found 7 papers, 1 papers with code
A Novel Approach to Regularising 1NN classifier for Improved Generalization
In this paper, we propose a class of non-parametric classifiers, that learn arbitrary boundaries and generalize well.
Decoupling Quantile Representations from Loss Functions
The simultaneous quantile regression (SQR) technique has been used to estimate uncertainties for deep learning models, but its application is limited by the requirement that the solution at the median quantile ({\tau} = 0. 5) must minimize the mean absolute error (MAE).
A Robust Morphological Approach for Semantic Segmentation of Very High Resolution Images
In this article, we develop a robust pipeline based on mathematical morphological (MM) operators that can seamlessly extend any existing semantic segmentation algorithm to high resolution images.
ESW Edge-Weights : Ensemble Stochastic Watershed Edge-Weights for Hyperspectral Image Classification
In this article, we estimate the edge-weights explicitly and use them for the downstream classification tasks - both semi-supervised and unsupervised.
Higher-Order Relations Skew Link Prediction in Graphs
In this article, we investigate this problem in the presence of higher-order relations.
A Theoretical Analysis of Granulometry-based Roughness Measures on Cartosat DEMs
One of the useful geophysical features of a river sub-basin is that of a roughness measure on DEMs.
Triplet-Watershed for Hyperspectral Image Classification
In this article, we propose to use a watershed classifier.
