Abstract: The rapid pace of urbanization underscores the importance of waste monitoring and management in urban planning and environmental conservation. Remote sensing technology enables the aerial ...

Abstract: Offset-based representation has emerged as a promising approach for modeling semantic relations between pixels and object motion, demonstrating efficacy across various computer vision tasks.

Abstract: Integration of complementary information from different modalities and efficient computation is crucial in remote sensing (RS) image classification applications. Convolutional neural ...

Abstract: Precise estimation of both state-of-charge (SoC) and state-of-health (SoH) is crucial for optimizing electric vehicle (EV) performance and enhancing the battery lifetime, safety, and ...

Abstract: Time series classification is an important task in time series data mining, and has attracted great interests and tremendous efforts during last decades. However, it remains a challenging ...

Abstract: Multimodal federated learning (FL) targets the intersection of two promising research directions in Internet of Things (IoT) scenarios: 1) leveraging complementary multimodal information to ...

Abstract: The enhancement of underwater images has emerged as a significant technological challenge in advancing marine research and exploration tasks. Due to the scattering of suspended particles and ...

Abstract: The joint optimization of production scheduling and resource constraints is critical to modern manufacturing systems. The number of auxiliary resources (fixtures) is usually insufficient in ...

Abstract: Recently, Optimal Transport has been proposed as a probabilistic framework in Machine Learning for comparing and manipulating probability distributions. This is rooted in its rich history ...

Abstract: This study investigates the impact of artificial general intelligence (AGI)-assisted project-based learning (PBL) on students’ higher order thinking and self-efficacy. Based on input from 17 ...

Abstract: Accurate pedestrian trajectory prediction is a crucial task for ensuring the safety of autonomous driving. However, most of the existing methods only model pedestrian trajectories in the ...