Research on Daily Objects Detection Based on Deep Neural Network
With the rapid development of deep learning,great breakthroughs have been made in the field of object detection.In this article,the deep learning algorithm is applied to the detection of daily objects,and some progress has been made in this direction.Compared with traditional object detection methods,the daily objects detection method based on deep learning is faster and more accurate.The main research work of this article: 1.collect a small data set of daily objects; 2.in the TensorFlow framework to build different models of object detection,and use this data set training model; 3.the training process and effect of the model are improved by fine-tuning the model parameters.
Sheng Ding Kun Zhao
Key Laboratory of Fiber Optic Sensing Technology and Information Processing,Ministry of Education,Wu Fiberhome Telecommunication Technologies Co.,Ltd,Wuhan,China
国际会议
上海
英文
1-5
2017-12-28（万方平台首次上网日期，不代表论文的发表时间）