Abstract: Mobile robots and autonomous vehicles rely on 3-D point cloud technology for environmental perception, which often employ various visual perception sensors within their Internet of Things ...

Abstract: Point cloud semantic segmentation has achieved considerable progress in the past decade. To alleviate expensive data annotation efforts, weakly supervised learning methods are preferable, ...

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DataCamp is geared towards data science and analytics, offering specialized Python tracks with practical exercises using ...

Abstract: This work presents a special unified compute-in-memory (CIM) processor supporting both general-purpose computing and deep neural network (DNN) operations, referred to as the general-purpose ...

Abstract: Point cloud analysis (such as 3D segmentation and detection) is a challenging task, because of not only the irregular geometries of many millions of unordered points, but also the great ...

Abstract: This WIP paper presents new research on exploratory learning, an educational technique that reverses the order of standard lecture-based instruction techniques. In exploratory learning, ...

Abstract: This paper examines a contextual paradigm for energy disaggregation using Non-Intrusive Load Monitoring (NILM). Due to numerous issues including low sampling rates, missing data, misaligned ...

Abstract: Self-supervised learning has achieved significant success in various fields such as point cloud detection and segmentation. However, self-supervised learning for point cloud registration is ...

Abstract: Generative artificial intelligence (GenAI) is emerging as a transformative technology in higher education, particularly in programming instruction. However, its impact on learning, ...

Abstract: Teloprogramo is an innovative web platform that enhances programming education by leveraging artificial intelli-gence to improve student outcomes. Built on prior technological advancements ...