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: 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 ...

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Abstract: Change detection has become a crucial topic in the field of remote sensing deep learning due to its extensive application in earth observation. However, real remote sensing images often ...