Sökning: "Icke-maximal undertryckning"

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  1. 1. Efficient and robust reduction of bounding boxes of a multi-class neural network’s output for vehicular radar-systems

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Elazab Gasser; [2022]
    Nyckelord :Non-maximum suppression; Deep Learning; Machine Learning; Autonomous Vehicles; Determinantal Point Process; Icke-maximal undertryckning; Djupinlärning; Maskininlärning; Autonoma fordon; Determinant punktprocess;

    Sammanfattning : Object detection has been a fundamental part of many emerging technologies, such as autonomous vehicles, robotics, and security. As deep learning is the main reason behind the leap of performance in object detection, it has mostly been associated with a post-processing step of non-maximum suppression (NMS) to reduce the number of resulting bounding boxes output from the network to, ideally, one box per object. LÄS MER