Abstract: Brain–computer interface (BCI) is an important way of human-computer interaction, with the ability to monitor brain states, and it has become an increasingly significant research direction.

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 ...

Local cell densities and positioning within cellular monolayers and stratified epithelia have important implications for cell interactions and the functionality of various biological processes. To ...

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, ...

1 Department of Computer Science, Dilla University, Dilla, Ethiopia. 2 Department of Computer Science, Addis Ababa University, Addis Ababa, Ethiopia. 3 Department of Agricultural and Biological ...

In recent years, more and more deep learning frameworks are being applied to hyperspectral image classification tasks and have achieved great results. However, the existing network models have higher ...

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 ...