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Efficient Post-Contour Correctness in Object Detection and Segmentation

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posted on 2020-01-14, 16:59 authored by Than LeThan Le
In this paper, we propose the simple method to optimize the datasets noise under the uncertainty applied to many applications in industry. Specifically, we use firstly the deep learning module at transfer learning based on using the mask-rcnn to detect the objects and segmentation effectively, then return the contours only. After that we address the shortest path for reduce the noise in order to increasing the highspeed in industrial applications. We illustrate adaptive many applications web applications such as mobile application where power computer is limited a source


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Submitting Author's Institution

University of Bordeaux, France

Submitting Author's Country

  • Viet Nam

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