People communicate with each other, sometimes face to face, sometimes with a text message or phone call. Cells also ...
Researchers developed a hybrid UMAP-HDBSCAN-SVM machine learning workflow to rapidly classify low-loss STEM-EELS spectrum ...
Abstract: A novel superpixel-based discriminative sparse model (SBDSM) for spectral-spatial classification of hyperspectral images (HSIs) is proposed. Here, a superpixel in a HSI is considered as a ...
Obtaining accurate, up-to-date information from fire-affected areas is essential not only to better understand air quality, biogeochemical cycles or climate, but also to contribute towards fire ...
The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...
Aimed at the hyperspectral image (HSI) classification under the condition of limited samples, this paper designs a joint spectral–spatial classification network based on metric meta-learning. First, ...
Abstract: Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral ...
Machine learning is a branch of artificial intelligence that includes methods, or algorithms, for automatically creating models from data. Unlike a system that performs a task by following explicit ...
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