2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)最新文献

Feature matching using sequential evaluation on sample consensus 基于样本一致性的序列评价特征匹配

2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2017-12-01 DOI: 10.1109/SPAC.2017.8304294

Chao-xia Shi, Yanqing Wang, Li He

引用次数: 2

Cooperative motion control method for humanoid robot based on SOCP 基于SOCP的仿人机器人协同运动控制方法

2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2017-12-01 DOI: 10.1109/SPAC.2017.8304321

Zhong Qiu-bo

引用次数: 1

Forecast customer flow using long short-term memory networks 使用长短期记忆网络预测客流量

2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2017-12-01 DOI: 10.1109/SPAC.2017.8304251

Zongming Yin, Junzhang Zhu, Xiaofeng Zhang

引用次数: 3

Broad learning system: Structural extensions on single-layer and multi-layer neural networks 广义学习系统:单层和多层神经网络的结构扩展

2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2017-12-01 DOI: 10.1109/SPAC.2017.8304264

Zhulin Liu, C. L. P. Chen

引用次数: 39

Distributed randomized singular value decomposition using count sketch 基于计数草图的分布随机奇异值分解

2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2017-12-01 DOI: 10.1109/SPAC.2017.8304273

Hongwe Chen, Jie Zhao, Qixing Luo, Yajun Hou

{"title":"Distributed randomized singular value decomposition using count sketch","authors":"Hongwe Chen, Jie Zhao, Qixing Luo, Yajun Hou","doi":"10.1109/SPAC.2017.8304273","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304273","url":null,"abstract":"Compared with other recommendation algorithms, Matrix decomposition is frequently used in the current recommendation system. It can not only lead to better results, but also can fully take the influence of various factors into account, which explains its good scalability. Matrix decomposition includ-es SVD(Singular Value Decomposition), non-negative matrix decomposition, Latent Factor Model and some other traditional matrix decomposition techniques is designed to approximate a high-dimensional matrix with low-dimensional. As a perfect technique in recommendation system, SVD is traditionally expert at dense matrix decomposition. However, real rating matrix are sparse, and have high time complexity of SVD, if the matrix size increases rapidly, the efficiency must become unacceptable. The combination of random algorithm and matrix decomposition turns traditional matrix decomposition into random matrix decomposition technique under distributed system environment. The random singular value decomposition technique illustrated in the following content can be at the expense of little accuracy under the premise of greatly improving the efficiency of the calculation.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122564638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Gender classification of full body images based on the convolutional neural network 基于卷积神经网络的全身图像性别分类

2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2017-12-01 DOI: 10.1109/SPAC.2017.8304366

Zhenxia Yu, Chengxuan Shen, Lin Chen

引用次数: 6

Reflective type blood oxygen saturation detection system based on MAX30100 基于MAX30100的反射式血氧饱和度检测系统

2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2017-12-01 DOI: 10.1109/SPAC.2017.8304350

Jiaxi Wan, Yuhua Zou, Ye Li, Jun Wang

{"title":"Reflective type blood oxygen saturation detection system based on MAX30100","authors":"Jiaxi Wan, Yuhua Zou, Ye Li, Jun Wang","doi":"10.1109/SPAC.2017.8304350","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304350","url":null,"abstract":"Oxygen is the key material to human's life, and oxygen saturation is one of the important indexes reflecting organic oxygen delivery status. Determining oxygen saturation in human blood by transmittance oxymetry is well developed as a monitoring technique, which is applied widely in clinical diagnosis or house health care. However, reflectance detecting is necessary in many circumstances, such as cerebral oxygen saturation, muscle oxygen saturation, or fetal oxygen saturation monitoring. So the reflective type oxygen saturation detection system gradually has become main flow of development. Based on the principle of oxygen saturation measurement, this paper introduces a blood oxygen saturation detection system design scheme based on the integrated chip MAX30100, which can simplify the circuit design, reduce system footprint, reduce the designing time and system power consumption. Through introduces the system hardware and software structure, signal processing methods and other aspects of the study to achieve the fingertip pulse signal acquisition and noise reduction processing. Through practical test, the system prototype machine realizes the function of pulse oxygen saturation detection.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130561602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 25

Discriminative multiview nonnegative matrix factorization with large margin for image classification 判别多视点大余量非负矩阵分解算法用于图像分类

2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2017-12-01 DOI: 10.1109/SPAC.2017.8304247

Fei Long, Weihua Ou, Kesheng Zhang, Yi Tan, Yunhao Xue, Gai Li

{"title":"Discriminative multiview nonnegative matrix factorization with large margin for image classification","authors":"Fei Long, Weihua Ou, Kesheng Zhang, Yi Tan, Yunhao Xue, Gai Li","doi":"10.1109/SPAC.2017.8304247","DOIUrl":"https://doi.org/10.1109/SPAC.2017.8304247","url":null,"abstract":"Image classification has attracted lots of attentions in recent years. To improve classification accuracy, multiple features are usually extracted to represent the context of images, which imposes a challenge for the combination of those features. To address this problem, we present a discriminative nonnegative multi-view learning approach for image classification based on the observation that those features are often nonnegative. For discrimination, we utilize class label as an auxiliary information to learn discriminative common representations through a set of nonnegative basis vectors with large margin. Meanwhile, view consistency constraint is imposed on the low-dimensional representations and correntropy-induced metric (CIM) is adopted for the measurement of reconstruction errors. We utilized half-quadratic optimization technique to solve the optimization problem and obtain an effective multiplicative update rule. Experimental results demonstrate the learned common latent representations by the proposed method are more efficient than other methods.","PeriodicalId":161647,"journal":{"name":"2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127046099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Emotional contagion and personality driven multi-robot task allocation algorithm 情绪传染与人格驱动的多机器人任务分配算法

2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2017-12-01 DOI: 10.1109/SPAC.2017.8304330

Baofu Fang, Zaijun Wang, Yong Li, Wang Hao

引用次数: 0

Multi-angle SAR image fusion algorithm based on visibility classification of non-layover region targets 基于非停留区域目标可见性分类的多角度SAR图像融合算法

2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC) Pub Date : 2017-12-01 DOI: 10.1109/SPAC.2017.8304355

Shibing Zhu, Da Ran

引用次数: 5