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服务机器人视觉目标感知研究 学位论文
博士, 沈阳: 中国科学院沈阳自动化研究所, 2017
Authors:  张强
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服务机器人  误匹配剔除  多目标实例  抓取检测  手眼标定  
基于支持向量机的多元过程质量诊断研究与应用 学位论文
硕士, 沈阳: 中国科学院沈阳自动化研究所, 2017
Authors:  蔡亚军
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多元统计过程控制  支持向量机  异常诊断  主元分析  质量管理系统  
基于多元统计分析的过程监测研究 学位论文
硕士, 沈阳: 中国科学院沈阳自动化研究所, 2017
Authors:  王中伟
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主元分析方法  支持向量数据描述  谱聚类  多模态过程监测  局部-全局模型  
PCA-based denoising method for division of focal plane polarimeters 期刊论文
Optics Express, 2017, 卷号: 25, 期号: 3, 页码: 2391-2400
Authors:  Zhang JC(张俊超);  Luo HB(罗海波);  Liang, Rongguang;  Zhou, Wei;  Hui B(惠斌);  Chang Z(常铮)
View  |  Adobe PDF(2192Kb)  |  Favorite  |  View/Download：343/69  |  Submit date：2017/02/18
Dimensionality Reduction on Grassmannian: A Good Practice 会议论文
Proceedings of 2017 International Conference on Intelligent Computing and Information Systems (ICIS 2017), Harbin, China, December 29-31, 2017
Authors:  Liu TC(刘天赐);  Shi ZL(史泽林);  Liu YP(刘云鹏);  Li CX(李晨曦)
View  |  Adobe PDF(708Kb)  |  Favorite  |  View/Download：58/2  |  Submit date：2018/12/24
Grassmann manifold  Riemannian optimization  image-set recognition  dimensionality reduction  
A Deep Face Recognition Method Based on Model Fine-tuning and Principal Component Analysis 会议论文
2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017, Hawaii, USA, July 31 - August 4, 2017
Authors:  Zhang YA(张延安);  Wang, HY(王宏玉);  Xu F(徐方);  Jia K(贾凯)
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Face Recognition  Deep Learning  Model Fine-tuning  Principal Component Analysis  Convolutional Neural Networks  
基于深度卷积神经网络与中心损失的人脸识别 期刊论文
科学技术与工程, 2017, 卷号: 17, 期号: 35, 页码: 92-97
Authors:  张延安;  王宏玉;  徐方
View  |  Adobe PDF(809Kb)  |  Favorite  |  View/Download：174/20  |  Submit date：2018/01/25
人脸识别  卷积神经网络  深度学习  中心损失  度量学习  主成分分析  
RNN-based Method for Fault Diagnosis of Grinding System 会议论文
2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017, Hawaii, USA, July 31 - August 4, 2017
Authors:  Qu XY(曲星宇);  Zeng P(曾鹏);  Xu, Chengcheng;  Fu, Dong-Dong
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Fault Diagnosis  Deep Learning  Rnn- Lstm  Autoencoder  
A method derived from genetic algorithm, principal component analysis and artificial neural networks to enhance classification capability of laser-Induced breakdown spectroscopy 会议论文
AOPC 2017: Optical Spectroscopy and Imaging, Beijing, China, June 4-6, 2017
Authors:  Zhang P(张鹏);  Sun LX(孙兰香);  Kong HY(孔海洋);  Yu HB(于海斌);  Guo MT(郭美亭);  Zeng P(曾鹏)
View  |  Adobe PDF(863Kb)  |  Favorite  |  View/Download：173/28  |  Submit date：2018/02/24
Laser Induced Breakdown Spectroscopy  Genetic Algorithm  Principal Component Analysis  Artificial Neural Networks  Spectral Segment Selection  Classification  
CSDM: Fusion of orthographic contour signature and distribution matrix for 3D object global representation and object recognition 会议论文
Proceedings of the 2017 IEEE International Conference on Robotics and Biomimetics, Macau, China, December 5-8, 2017
Authors:  Fu ML(付明亮);  Luo HT(骆海涛);  Zhou WJ(周维佳)
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Global Feature Descriptor  Point Cloud  Projection Statistics  Object Recognition