Abstract: Reinforcement learning (RL) has shown remarkable success in solving complex decision-making and control tasks. However, many model-free RL algorithms experience performance degradation due ...

Abstract: In the context of rapid advancements in artificial intelligence (AI), enhancing AI literacy among college students is crucial for promoting the sustainable development of higher education.

Abstract: Object detection plays a key role in helping to enable industrial quality control and safety monitoring. This article introduces a lightweight and efficient transformer-based object ...

Abstract: The widespread presence of oceanic internal waves (IWs) across continental shelves, straits, and islands has been confirmed using multiple satellite payloads, including optical and synthetic ...

Abstract: In this paper, we analyse two well-known objective image quality metrics, the peak-signal-to-noise ratio (PSNR) as well as the structural similarity index measure (SSIM), and we derive a ...

Abstract: In this study, we propose Multimodal Fusion-supervised Cross-modality Alignment Perception (MulFS-CAP), a novel framework for single-stage fusion of unregistered infrared-visible images.

Abstract: The future sixth-generation (6G) of wireless networks is expected to surpass its predecessors by offering ubiquitous coverage through integrated air-ground deployments in both communication ...

Abstract: The infrared small and dim (S&D) target detection is one of the key techniques in the infrared search and tracking system. Since the local regions similar to infrared S&D targets spread over ...

Abstract: Owing to the success of transformer models, recent works study their applicability in 3D medical segmentation tasks. Within the transformer models, the self-attention mechanism is one of the ...

Abstract: Federated learning (FL) is a distributed machine learning paradigm allowing multiple clients to collaboratively train a global model without sharing their local data. However, FL entails ...

Abstract: This study presents a multimodal human-exoskeleton cooperative control method to realize different control modes smoothly switching each other with satisfactory stable performance.

Abstract: Snapshot Spectral Imaging (SSI) techniques, with the ability to capture both spectral and spatial information in a single exposure, have been found useful in a wide range of applications.