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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作,涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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    DEEP LEARNING-BASED OBSTACLE DETECTION AND DEPTH ESTIMATION
    (2019-01-01)
    Hsieh, Yi-Yu
    ;
    Lin, Wei-Yu
    ;
    Li, Dong-Lin
    ;
    Chuang, Jen-Hui
    ;
    資訊工程學系
    This paper proposed a modified YOLOv3 which has an extra object depth prediction module for obstacle detection and avoidance. We use a pre-processed KITTI dataset to train the proposed, unified model for (i) object detection and (ii) depth prediction and use the AirSim flight simulator to generate synthetic aerial images to verify that our model can be applied in different data domains. Experimental results show that the proposed model compares favorably with other depth map prediction methods in terms of accuracy in the prediction of object depth for pre-processed KITTI dataset, while the unified approach can actually improve both (i) and (ii) at the same time.