华中科技大学学报（自然科学版）2017，Vol.45Issue(10)：7-11,5.DOI:10.13245/j.hust.171002
基于卷积神经网络的目标识别及姿态检测
Object identification and pose detection based on convolutional neural network
摘要
Abstract
Aiming at the characteristics of micro-assembly system target ,a network was trained based on deep learning method and the faster region-based convolutional neural network (faster R-CNN) ob-ject detection architecture and Zeiler and Fergus′s network (ZFNet) convolutional neural network were used .A pose detection network was designed for recognizing targets .The experimental results show that the proposed deep learning method can effectively identify and detect the partially occluded objects ,and compared with the traditional method ,this method has strong adaptability to environ-ment and speediness with practical application value .关键词
微装配系统/卷积神经网络/显微视觉/目标识别/姿态检测Key words
micro-assembly system/convolutional neural network/micro-vision/object identifica-tion/pose detection分类
信息技术与安全科学引用本文复制引用
黄心汉,苏豪,彭刚,熊超..基于卷积神经网络的目标识别及姿态检测[J].华中科技大学学报（自然科学版）,2017,45(10):7-11,5.基金项目
国家自然科学基金资助项目 (60275013) （60275013）
国家高技术研究发展计划资助项目 (2008AA8041302) . （2008AA8041302）
