Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (9): 182-190.DOI: 10.3778/j.issn.1002-8331.1912-0403

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End to End Object Recognition Algorithm for Multi-attributes of Multi-values

ZHOU Lungang, SUN Yifeng, WANG Kun, WU Jiang, HUANG Weigui, LI Binglong   

  1. 1.Henan Industrial School, Zhengzhou 450002, China
    2.Information Engineering University, Zhengzhou 450001, China
    3.Zhengzhou Xinda Institute of Advanced Technology, Zhengzhou 450001, China
  • Online:2021-05-01 Published:2021-04-29



  1. 1.河南省工业学校,郑州 450002
    2.信息工程大学,郑州 450001
    3.郑州信大先进技术研究院,郑州 450001


In order to improve image object recognition speed for multi-attributes of multi-values, an end-to-end recognition algorithm is proposed. Firstly, the modified YoloV3 network is used as main network in order to detect the object bounding boxes. Sub-networks are constructed according to the independent attributes. Sub-networks share the deep bounding box features of main network and adopt multi-outputs to recognize the attributes multi-values. There are three stages with different objective functions in the training process. Experimental results show that the proposed algorithm has good performance.

Key words: object detection, attribute recognition, deep learning, convolutional neural network, image recognition



关键词: 目标检测, 属性识别, 深度学习, 卷积神经网络, 图像识别