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    Openset Approach To Object Detection, An

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    https://hdl.handle.net/10976/167065
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    Abstract
    Object detection has been a popular area of research in computer vision, where during the recent years deep learning based approaches have taken over the traditional approaches based on hand engineered features like HOG and SIFT. A common aspect in all of these recent approaches has been the approach taken to identify parts of an image as backgrounds. This approach generally limits the performance of such a deep learning approach when it is applied outside the academic datasets into the real world. We highlight this performance gap by simulating a real-world detection problem using our novel ...
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    Author(s)
    Dhamija, Akshay Raj

    Advisor(s)
    Boult, Terrance E.

    Date Submitted
    2018-12
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