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: 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: The forthcoming generation of wireless technology, 6G, promises a revolutionary leap beyond traditional data-centric services. It aims to usher in an era of ubiquitous intelligent services, ...

Abstract: Infrared and visible image fusion is currently an important research direction in the field of multimodal image fusion, which aims to utilize the complementary information between infrared ...

Abstract: Obstacle avoidance for Unmanned Aerial Vehicles (UAVs) in cluttered environments is significantly challenging. Existing obstacle avoidance for UAVs either focuses on fully static ...

Abstract: In this paper, we investigate the tracking issue for fully actuated systems (FASs) with parameter uncertainties and input quantization. Different from models of the existing adaptive control ...

Abstract: Low-light image enhancement (LIE) aims to restore images taken under poor lighting conditions, thereby extracting more information and details to robustly support subsequent visual tasks.

Abstract: In featureless point clouds, such as cylinder-ruled surfaces or shapes with lots of flattened areas, we observe that some classic iterative closest point variants, including point-to-point, ...

Abstract: Analog computing in memory (CIM) based on resistive nonvolatile memory (NVM) has encountered several issues, such as low parallelism, low computing accuracy, and considerable power ...

Abstract: This paper presents a combined control method of resonant frequency tracking and CC/CV charging mode for undersea wireless power transfer (UWPT) systems. This control method can quickly ...

Abstract: Searching dynamic targets in unknown underwater environments is quite challenging for multiple autonomous underwater vehicles (AUVs) due to the limited stability of underwater communications ...

Abstract: Object detection and recognition (OD&R) based on deep learning is a hot topic in the application of synthetic aperture radar (SAR). These methodologies based on deep learning are inherently ...