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Found 4 papers, 2 papers with code
HyperMask: Adaptive Hypernetwork-based Masks for Continual Learning
In the paper, we propose a method called HyperMask, which trains a single network for all CL tasks.
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.
Hard hat wearing detection based on head keypoint localization
In recent years, a lot of attention is paid to deep learning methods in the context of vision-based construction site safety systems, especially regarding personal protective equipment.
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.
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