Showing 521 - 540 results of 593 for search '(((pinn OR pink) OR (pinge OR inge)) OR (((spingna OR sspingna) OR sspinna) OR ping))', query time: 0.15s Refine Results
  1. 521

    Object-oriented indoor navigation for delivery robot by Li, Yuanwei

    Published 2024
    “…The emergence of BERT models also help in training and construct ing navigation frameworks. Although the BERT model has good performance in VLN, the mismatch between instructions and visual information at the input leads to navigation errors for robots in similar scenes. …”
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    Thesis-Master by Coursework
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    Performance in the wartime archive : Michio Ito at the Alien Enemy Hearing Board by Riordan, Kevin

    Published 2020
    “…In the documents establishing his detention, the Alien Enemy Hear-ing Board found Ito to be “an artist of artistic temperament, striking appear-ance, fine manners, cultured, educated and capable of any and all sorts of pro-paganda, espionage and sabotage.”3 In this essay, I interrogate this sentence’s central conjunction, the grammatical choreography that links art, culture, and education to propaganda, espionage, and sabotage.…”
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    Journal Article
  8. 528

    Influence of admixture on 3D printable construction material by Tay, Daniel Yi Wei, Tan, Ming Jen

    Published 2020
    “…The use of oscillatory test helps to identify the nature of the s1J'uctur:ing mechanisms present in the material which is useful when attempting in understanding the flow behavior of the material.…”
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    Conference Paper
  9. 529

    Order statistics based sampling design for reliability sampling by Low, Chan Kee, Balasooriya, Uditha

    Published 2008
    “…We consider the problem of designing variables-sampling plans for life test-ing. Leiberman and Resnikoff, Schneider and many others have considered this problem for location-scale type lifetime distributions. …”
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    Research Report
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    A survery on CNN transfer learning for image classification by Teo, Jia Sheng

    Published 2023
    “…In addition, the author has made a comparison with 15 pre-trained Transfer Learn- ing models. From the comparisons done on the small food dataset and a larger sized Caltech101 dataset, the author concluded that the dataset is one of the main deter- minants of a model’s performance, and deeper CNN model architectures does not necessarily guarantee better results.…”
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    Final Year Project (FYP)
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