Fast object detection based on binary deep convolution neural networks | |
Sun, Siyang1; Yin, Yingjie1; Wang, Xingang1; Xu, De1,2; Gu, Qingyi1; Wu, Wenqi1 | |
刊名 | CAAI Transactions on Intelligence Technology |
2018-12 | |
卷号 | 3期号:4页码:191-197 |
关键词 | Object detection |
英文摘要 | In this study, a fast object detection algorithm based on binary deep convolution neural networks (CNNs) is proposed. Convolution kernels of different sizes are used to predict classes and bounding boxes of multi-scale objects directly in the last feature map of a deep CNN. In this way, rapid object detection with acceptable precision loss is achieved. In addition, binary quantisation for weight values and input data of each layer is used to squeeze the networks for faster object detection. Compared to full-precision convolution, the proposed binary deep CNNs for object detection results in 62 times faster convolutional operations and 32 times memory saving in theory, what’s more, the proposed method is easy to be implemented in embedded computing systems because of the binary operation for convolution and low memory requirement. Experimental results on Pascal VOC2007 validate the effectiveness of the authors’ proposed method. |
语种 | 英语 |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/39055] |
专题 | 精密感知与控制研究中心_精密感知与控制 |
通讯作者 | Wang, Xingang |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Science |
推荐引用方式 GB/T 7714 | Sun, Siyang,Yin, Yingjie,Wang, Xingang,et al. Fast object detection based on binary deep convolution neural networks[J]. CAAI Transactions on Intelligence Technology,2018,3(4):191-197. |
APA | Sun, Siyang,Yin, Yingjie,Wang, Xingang,Xu, De,Gu, Qingyi,&Wu, Wenqi.(2018).Fast object detection based on binary deep convolution neural networks.CAAI Transactions on Intelligence Technology,3(4),191-197. |
MLA | Sun, Siyang,et al."Fast object detection based on binary deep convolution neural networks".CAAI Transactions on Intelligence Technology 3.4(2018):191-197. |
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