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 three-point contest is a staple of NBA All-Star weekend. Even in the years where the dunk contest got most of the glitz and glamour the three-point contest would deliver great competition and an ...

Turning Point USA first announced its alternative to the NFL's official Super Bowl Halftime Show in October. By Jessica Nicholson As Super Bowl LX draws near on Feb. 8, millions of sports fans are ...

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 ...