Abstract: Removing adverse weather conditions like rain, fog, and snow from images is an important problem in many applications. Most methods proposed in the literature have been designed to deal with ...

Abstract: The progress of brain cognition and learning mechanisms has provided new inspiration for the next generation of artificial intelligence (AI) and provided the biological basis for the ...

Abstract: In this paper, we investigate the integration of integrated sensing and communication (ISAC) and reconfigurable intelligent surfaces (RIS) for providing wide-coverage and ultra-reliable ...

Abstract: A vision-based tactile sensor (VBTS) is an innovative optical sensor widely applied in robotic perception. The VBTS consists of a contact module, an illumination module, and a camera module.

Abstract: Space-Air-Ground Integrated Networks (SAGIN) is considered as the key structure of the next generation network. The space satellites and air nodes are potential candidates to assist and ...

Abstract: Modern industrial processes often operate under different modes, which brings challenges to model predictive control (MPC). Recently, most MPC related methods would establish prediction ...

Abstract: In recent years, the digital world has advanced significantly, particularly on the Internet, which is critical given that many of our activities are now conducted online. As a result of ...

Abstract: Class-incremental learning (CIL) enables models to continuously learn new classes while addressing catastrophic forgetting. With the introduction of pre-trained models, new tuning paradigms ...

Abstract: The predictive learning of spatiotemporal sequences aims to generate future images by learning from the historical context, where the visual dynamics are believed to have modular structures ...

Abstract: Unsupervised monocular depth estimation plays a vital role for endoscopy-based minimally invasive surgery (MIS). However, it remains challenging due to the distinctive imaging ...

Abstract: For significant memory concern (SMC) and mild cognitive impairment (MCI), their classification performance is limited by confounding features, diverse imaging protocols, and limited sample ...

Abstract: This study investigates a fuzzy consensus problem for nonlinear multi-agent systems (MASs) with parameter uncertainties via dynamic event-triggered mechanism. The interval type-2 (IT2) fuzzy ...