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方法:YOLO V3是当前目标检测算法中检测召回率高且速度较优的算法,但在定位上不够准确.为解决该问题,本文采用流行排序算法对得到的检测框进行二次修正,从而使得目标定位精度提升.结果:通过结合YOLO V3和流行排序算法使目标检测框的交并比提升了3%～9%.结论:通过YOLO V3和Ranking Saliency的结合能够使得目标检测的...
The global top 5 universities (Harvard University, Stanford University, University of Cambridge, Massachusetts Institute of Technology [MIT], and University of California, Berkeley [UCB]) and top 21–25 universities (i.e., ETH Zurich, University of Toronto, Washington University in St. Louis, The...