Visual BCIs based on steady-state visual evoked potentials (SSVEPs) have long been the gold standard for high-speed noninvasive brain-computer ...
Figures 12-14 are the land use/land cover maps of existing forest reserves in the FCT, namely; Tufa in Abaji, Chihuma, Chikwei, Kusoru and Shaba in Bwari, Maje Abuchi in Gwagwalada, then, Buga Hill, ...
Abstract: Urban vegetation classification is challenging due to the heterogeneous nature of urban environments. Accurate mapping of urban vegetation, which plays a crucial role in regulating ...
Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...
Abstract: Objective: Brain-computer interfaces (BCIs) based on event-related potentials (ERPs) are among the most accurate and reliable BCIs. However, current mainstream classification algorithms ...