Abstract: Hyperspectral image (HSI) classification faces critical challenges in effectively modeling the intricate spectral–spatial structures and non-Euclidean relationships. Traditional methods ...
WASHINGTON, Dec 10 (Reuters) - U.S. President Donald Trump said on Wednesday the news network CNN should be sold as part of a deal for its parent company Warner Bros Discovery (WBD.O), opens new tab ...
Lloyd’s Register (LR) and Latsco have successfully completed a proof-of-concept for a new standard in digital class assurance with data-driven surveys. This collaboration aims to demonstrate how ...
The Cleveland Browns are having to find some hidden gems on the bench with the latest injuries to the offensive line affecting the lineup. If the Cleveland Browns already didn't have enough problems ...
Nicole Charky-Chami is a senior editor based in Los Angeles, writing and producing breaking news. She teaches journalism courses for UCLA Extension and previously taught at Loyola Marymount University ...
Hyperspectral image (HSI) classification aims at categorizing each pixel in an HSI, facilitating precise identification and differentiation of various land cover types. In recent years, graph neural ...
Abstract: Active learning (AL) has achieved great success in remotely sensed hyperspectral image (HSI) classification due to its ability to select highly informative training samples. An appropriate ...
Abstract: Deep reinforcement learning (DRL) is a powerful method for local motion planning in automated driving. However, training of DRL agents is difficult and subject to instability. We propose ...
Abstract: Graph convolutional neural networks have demonstrated promising solutions for processing non-Euclidean data in tasks such as node classification. While existing graph convolution models aim ...
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