Abstract: Semantic change detection (SCD) refers to the task of simultaneously extracting changed areas and their semantic categories (before and after the changes) in remote sensing images (RSIs).

Abstract: Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted images, since it maintains the excellent property that the original cover can be losslessly recovered ...

Abstract: Self-driving vehicles are a maturing technology with the potential to reshape mobility by enhancing the safety, accessibility, efficiency, and convenience of automotive transportation.

Abstract: An active security control approach is developed in this article for cyber-physical systems (CPSs) under denial-of-service (DoS) attacks, where DoS attacks exist in both the ...

Abstract: Reports the completion of four fundamental fluidic operations considered essential to build digital microfluidic circuits, which can be used for lab-on-a-chip or micro total analysis system ...

Abstract: This article studies the stability control problem of uncertain nonlinear systems with unknown multiple classes of actuator faults. We investigate not only traditional actuator gain and bias ...

Abstract: A high-precision feature extraction model is crucial for change detection (CD). In the past, many deep learning-based supervised CD methods learned to recognize change feature patterns from ...

Abstract: Collecting airborne and spaceborne intelligence, surveillance, and reconnaissance (ISR) information is mandatory for addressing the defense challenges posed in the 21st century. A key tool ...

Abstract: The wireless power transfer (WPT) system based on the parity-time (PT) symmetry has been proved to be a promising WPT system due to its characteristics of constant efficiency and output ...

Abstract: The sparse characteristics of target features poses significant challenges when using deep learning methods for infrared dim small targets. To tackle this issue, this article proposes a ...

Abstract: Emotion recognition based on electroencephalogram (EEG) is fundamentally associated with human-like intelligence system. However, due to the noise-sensitive characteristics of EEGs and the ...

Abstract: In this paper, a new control mechanism for the variable forgetting factor (VFF) of the recursive least square (RLS) adaptive algorithm is presented. The control algorithm is basically a ...