2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics最新文献

Underwater Target Recognition Based on Module Time-frequency Matrix 基于模时频矩阵的水下目标识别

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2012-09-20 DOI: 10.1109/IHMSC.2012.16

Xi Xu, Min Shi

引用次数: 0

Obstacle Detection of a Novel Travel Aid for Visual Impaired People 一种视障人士旅行辅助设备的障碍物检测

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2012-09-20 DOI: 10.1109/IHMSC.2012.182

Ying Jie, Song Yanbin

引用次数: 12

An Adaptive Object Detection Scope Algorithm Based on SIFT 基于SIFT的自适应目标检测范围算法

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2012-08-26 DOI: 10.1109/IHMSC.2012.120

Yuanyuan Lu, Xiangyang Xu, Y. Dai, Bin Zheng

引用次数: 5

Research of Input and Output Technology Based on Virtualized Cluster 基于虚拟化集群的输入输出技术研究

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2012-08-26 DOI: 10.1109/IHMSC.2012.43

Yan Zhang, Lixin Xu, Shichun Pang

引用次数: 1

Power-down Protection Technology in Embedded System 嵌入式系统中的掉电保护技术

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2012-08-26 DOI: 10.1109/IHMSC.2012.139

Hongbo Yu, Yihua Lan, H. Ren, Yi Chen

引用次数: 1

Computing a Separating Element for a Zero Dimensional Parametric Algebraic Variety 零维参数代数变量分离元的计算

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2012-08-26 DOI: 10.1109/IHMSC.2012.164

Chang Tan, Jun Cao, Xiuhuan Ding

引用次数: 0

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2012-08-26 DOI: 10.1109/IHMSC.2012.185

Yihua Lan, H. Ren, Yong Zhang, Hongbo Yu

{"title":"Similarity in Mammography CAD Using CBIR Approach: A Validation Study","authors":"Yihua Lan, H. Ren, Yong Zhang, Hongbo Yu","doi":"10.1109/IHMSC.2012.185","DOIUrl":"https://doi.org/10.1109/IHMSC.2012.185","url":null,"abstract":"To provide assistance for radiologists in mammographic screening, many computer-aided detection and diagnosis systems (CAD) have been developed. However, there are a lot of problems which should be addressed in conventional mammographic CAD system, such as the relatively lower performance in detecting malignant masses, especially those subtle masses. The reasons which caused those errors may be the black-box type approach, which only cuing those suspicious masses but it is different to explain the reasoning of the CAD decision-making. Mammographic CAD using content-based image retrieval is another new type of CAD which can provide visual assistance instead of the type of black box method in conventional CAD for radiologists. Unlike those conventional CAD, in content-based image retrieval (CBIR) CAD, several most similar regions of interest (ROIs) are provided to radiologists as well as the decision index (DI) of one ROI which being a positive region. It has been proved that this visual aid tool could improve radiologists' performance. At present, there are two common types of CBIR CAD based on the calculation of similarity between testing ROI and reference ROI, one is the multi-feature based methods, and the other one is pixel-value-based template matching methods. The typical techniques used in these two types of CBIR CAD are multi-feature-based K-nearest neighbor (KNN) and template matching based system using mutual information (MI). The objective of this paper is to evaluate the performance of those methods commonly used in CBIR and discuss the approaches to improve CAD performance.","PeriodicalId":431532,"journal":{"name":"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"602 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123209353","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: 4

A New Fuzzy Control and Dynamic Modeling of Bicycle Robot 一种新的自行车机器人模糊控制与动态建模方法

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2012-08-26 DOI: 10.1109/IHMSC.2012.109

Y. Li, X. Ren, Jun Liu

{"title":"A New Fuzzy Control and Dynamic Modeling of Bicycle Robot","authors":"Y. Li, X. Ren, Jun Liu","doi":"10.1109/IHMSC.2012.109","DOIUrl":"https://doi.org/10.1109/IHMSC.2012.109","url":null,"abstract":"A dynamic model of bicycle robot is established based on the Lagrange method, and its motion features, which include nonlinear and parameter time-varying, are analyzed. A new fuzzy control is proposed to make the bicycle robot system achieve favorable control effects including good dynamic and steady-state performance. This new fuzzy control can be divided into two components. In the first part, the fuzzy control method, which is on the basis of the individual riding experience, is used to promote the dumping bicycle to swing back to the equilibrium position. In the second part, the adaptive fuzzy PID method is employed to eliminate static error and guarantee the bicycle robot no vibration near the equilibrium position. Concerning reliability of switching process, the fuzzy method of smooth switching is used to guarantee the steady transition between these two different control strategies. Since it is difficult to select the initial values of the adaptive fuzzy PID method, a modified particle swarm optimization (MPSO) method is utilized to optimize the initial parameters off-line. To show high efficiency and the accuracy of this proposed algorithm, simulation results demonstrate that the stability of bicycle robot can be guaranteed by using this design scheme.","PeriodicalId":431532,"journal":{"name":"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126728374","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: 6

Kalman Filter Method of Target Tracking Based on LOS Coordinate 基于LOS坐标的目标跟踪卡尔曼滤波方法

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2012-08-26 DOI: 10.1109/IHMSC.2012.66

Jun Wang, Liangxian Gu, Bo Wang, Ye Tian

引用次数: 0

Design and Implementation of UAV Intelligent Aerial Photography System 无人机智能航拍系统的设计与实现

2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics Pub Date : 2012-08-26 DOI: 10.1109/IHMSC.2012.144

Xin Li, Liang Yang

引用次数: 33