Jinxing Niu1,*, Qingsheng Hu1, Yi Niu1, Tao Zhang1, Sunil Kumar Jha2
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2221-2229, 2021, DOI:10.32604/cmc.2021.017073
Abstract Object recognition and location has always been one of the research hotspots in machine vision. It is of great value and significance to the development and application of current service robots, industrial automation, unmanned driving and other fields. In order to realize the real-time recognition and location of indoor scene objects, this article proposes an improved YOLOv3 neural network model, which combines densely connected networks and residual networks to construct a new YOLOv3 backbone network, which is applied to the detection and recognition of objects in indoor scenes. In this article, RealSense D415 RGB-D camera is used to obtain the… More >
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