Showing 10,281 - 10,300 results of 10,492 for search '(((((cheers OR cheaters) OR beers) OR car) OR peer) OR (chapter OR when))*', query time: 0.22s Refine Results
  1. 10281

    Salient keypoint detectors and compact feature descriptors for 3D perception by Prakhya, Sai Manoj

    Published 2017
    “…B-SHOT requires 32 times lesser memory for its representation while being 6 times faster in feature descriptor matching, when compared to the SHOT. Finally, for the applications that require online transfer of 3D descriptors over a network, there is a need to develop compressed 3D descriptors with even lower memory footprint, i.e., bandwidth and yet have high descriptiveness. …”
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    Thesis
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  5. 10285

    Using dynamic assessment of writing to promote technology-enhanced learning in higher education (Abstract) [Conference paper] by Meletiadou, Eleni

    Published 2023
    “…Round 1 (implicit) consisted solely of a scored and highlighted rubric, not identifying the location or nature of the erroneous parts and was provided by randomly chosen peers) via Padlet to ensure anonymity and allow students to experiment with digital platforms. …”
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    Conference or Workshop Item
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    Exploiting LoRaWAN for efficient and resilient IoT networks by Gu, Chaojie

    Published 2020
    “…The physical coupling of the two planes may lead to undesirable consequences. For example, when a node loses connections with its neighbors, the controller cannot reach the node anymore. …”
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    Thesis-Doctor of Philosophy
  18. 10298

    A combined numerical and experimental approach to investigations of body-freedom flutter on flying wings by Ang, Elijah Hao Wei

    Published 2024
    “…BTF and BFF experience different dominant modes while undergoing flutter, with BTF’s dominant mode being torsion and BFF being the rigid-body short period mode, resulting in lower BFF speeds when compared to BTF. In general, BTF speeds increase as weights are moved towards the wingtip or increasing tip weights, which increases the inertia of the system to enhance stability. …”
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    Thesis-Doctor of Philosophy
  19. 10299
  20. 10300

    Graph representation learning by Zhang, Xinyi

    Published 2022
    “…As for the node-level graph representation learning, traditional node-level representation learning methods focus more on homogeneous information networks (homogeneous graphs) and have achieved remarkable performance. However, when it takes different aspects of a graph into consideration, especially in heterogeneous information networks (HINs) where multiple types of nodes and edges should be considered, node-level representation learning methods designed for homogeneous information networks are suboptimal and fail to handle the semantic incompatibility brought from HIN. …”
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    Thesis-Doctor of Philosophy