Search Results for author:
Found 6 papers, 3 papers with code
Data structure > labels? Unsupervised heuristics for SVM hyperparameter estimation
Classification is one of the main areas of pattern recognition research, and within it, Support Vector Machine (SVM) is one of the most popular methods outside of field of deep learning -- and a de-facto reference for many Machine Learning approaches.
Improving Autoencoder Training Performance for Hyperspectral Unmixing with Network Reinitialisation
Neural networks, in particular autoencoders, are one of the most promising solutions for unmixing hyperspectral data, i. e. reconstructing the spectra of observed substances (endmembers) and their relative mixing fractions (abundances), which is needed for effective hyperspectral analysis and classification.
Hyperspectral classification of blood-like substances using machine learning methods combined with genetic algorithms in transductive and inductive scenarios
This study is focused on applying genetic algorithms (GA) to model and band selection in hyperspectral image classification.
Comparison of surface thermal patterns of horses and donkeys in IRT images
The aim was to find patterns in thermal images of donkeys and horses, and determine if these patterns share similarities.
Quantitative Methods
A Dataset for Evaluating Blood Detection in Hyperspectral Images
To facilitate their development, we present a new hyperspectral blood detection dataset.
Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images
In this paper we present an analysis of a general algorithm for band selection based on higher order cumulants.
