Abstract: Considering the impact of operation and maintenance costs and technology, there is generally a lack of sufficient meteorological observation devices within the distributed photovoltaic (PV) ...
Abstract: The ionosphere is vital for satellite navigation and radio communication, but observational limitations necessitate ionospheric forecasting. The least squares collocation (LSC) method is ...
Abstract: Change detection is a critical task in earth observation applications. Recently, deep-learning-based methods have shown promising performance and are quickly adopted in change detection.
Abstract: This article presents a new deep-learning architecture based on an encoder-decoder framework that retains contrast while performing background subtraction (BS) on thermal videos. The ...
Abstract: Infrared small target detection (IRSTD) is the challenging task of identifying small targets with low signal-to-noise ratios in complex backgrounds. Traditional methods in the complex ...
Abstract: Current methods for remote sensing image dehazing confront noteworthy computational intricacies and yield suboptimal dehazed outputs, thereby circumscribing their pragmatic applicability. To ...
Abstract: The current data scarcity problem in EEG-based emotion recognition tasks leads to difficulty in building high-precision models using existing deep learning methods. To tackle this problem, a ...
The lineup for Turning Point USA's "All-American Halftime Show" is finally here. The show, put on by the conservative organization to compete with Bad Bunny's Super Bowl halftime performance, will ...
Abstract: Community discovery is an essential research area with significant real-world applications. Lately, Graph Convolutional Networks (GCNs) have gained popularity for their ability to ...
Ayyoun is a staff writer who loves all things gaming and tech. His journey into the realm of gaming began with a PlayStation 1 but he chose PC as his platform of choice. With over 6 years of ...