Abstract: Deep learning has shown great potential in hyperspectral image (HSI) classification. However, training these models usually requires a large amount of labeled data. Since the collection of ...
In this era of digital transformation, buzzwords like ‘Industry 4.0’ and ‘digitalization’ have become part of our daily vocabulary. But behind these trendy terms lies a potent technological innovation ...
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 ...
Abstract: The idea of spatial correlation has been used in polarimetric synthetic aperture radar (PolSAR) classification for many years. It is common that the bigger the spatial correlation, the more ...
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, ...
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 ...
The Common Spatial Pattern (CSP) algorithm is an effective and popular method for classifying 2-class motor imagery electroencephalogram (EEG) data, but its effectiveness depends on the ...
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