Abstract: Infrared small target detection (ISTD) boasts extensive applications across civil and military domains, owing to its exceptional all-day performance. Neural network innovations have led to ...

Abstract: Coordinated navigation of an arbitrary number of robots to an arbitrary number of goals is a big challenge in robotics, often hindered by scalability limitations of existing strategies. This ...

Abstract: Satellite communication offers the prospect of service continuity over uncovered and under-covered areas, service ubiquity, and service scalability. However, several challenges must first be ...

Abstract: The author was led to the study given in this paper from a consideration of large scale computing machines in which a large number of operations must be ...

Book Abstract: This comprehensive guide offers a detailed treatment of the analysis, design, simulation and testing of the full range of today's leading delta-sigma data converters. Written by ...

Abstract: Local and global spectral and spatial information is crucial for hyperspectral image (HSI) classification. However, modeling the global context has been challenging due to the limitations of ...

Abstract: This review examines the ethical, social, and technical challenges posed by AI-generated text tools, focusing on their rapid advancement and widespread adoption. An exhaustive literature ...

Abstract: Efficient and accurate thermal prediction is important for the optimal design of HFTs. The configuration of HFTs is typically non-rotationally symmetrical. A three-dimensional (3D) finite ...

Abstract: Infrared-visible image fusion (IVIF) is a fundamental and critical task in the field of computer vision. Its aim is to integrate the unique characteristics of both infrared and visible ...

Abstract: Achieving comprehensive and accurate detection of battery anomalies is crucial for battery management systems. However, the complexity of electrical structures and limited computational ...

Abstract: Multi-view learning is a machine learning paradigm that utilizes multiple feature sets or data sources to improve learning performance and generalization. However, existing multi-view ...