2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)最新文献_第4页

A benchmark 3D fingerprint database 一个基准的3D指纹数据库

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980965

Wei Zhou, Jiankun Hu, Ian R. Petersen, Song Wang, Bennamoun

{"title":"A benchmark 3D fingerprint database","authors":"Wei Zhou, Jiankun Hu, Ian R. Petersen, Song Wang, Bennamoun","doi":"10.1109/FSKD.2014.6980965","DOIUrl":"https://doi.org/10.1109/FSKD.2014.6980965","url":null,"abstract":"Fingerprint biometric is one of the most successful biometrics applied in both forensic law enforcement and security applications. Recent developments in fingerprint acquisition technology have resulted in touchless live scan devices that generate 3D representation of fingerprints, and thus can overcome the deformation and smearing problems caused by conventional contact-based acquisition techniques. However, there are yet no 3D full fingerprint databases with their corresponding 2D prints for fingerprint biometric research. This paper presents a 3D fingerprint database we have established in order to investigate the 3D fingerprint biometric comprehensively. It consists of 3D fingerprints as well as their corresponding 2D fingerprints captured by two commercial fingerprint scanners from 150 subjects in Australia. Besides, we have tested the performance of 2D fingerprint verification, 3D fingerprint verification, and 2D to 3D fingerprint verification. The results show that more work is needed to improve the performance of 2D to 3D fingerprint verification. In addition, the database is expected to be released publicly in late 2014.","PeriodicalId":397095,"journal":{"name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128787786","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: 33

Rough approximations in tolerance rough set models 公差粗糙集模型中的粗糙近似

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980807

Jilin Huang, Yanyong Guan, Jianting Shen, Hongkai Wang

引用次数: 2

Mixture data-driven Takagi-Sugeno fuzzy model 混合数据驱动的Takagi-Sugeno模糊模型

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980801

Zhi-gang Su, B. Rezaee, Pei-hong Wang

{"title":"Mixture data-driven Takagi-Sugeno fuzzy model","authors":"Zhi-gang Su, B. Rezaee, Pei-hong Wang","doi":"10.1109/FSKD.2014.6980801","DOIUrl":"https://doi.org/10.1109/FSKD.2014.6980801","url":null,"abstract":"The conventional Takagi-Sugeno (T-S) fuzzy model is an effective tool used to approximating behaviors of nonlinear systems on the basis of precise and certain input and output observations. In some situations, however, we can only obtain mixture of precise data (for input variables), imprecise and uncertain data (for output variable/response). This paper presents a method used to constructing T-S fuzzy model in such case where the imprecise and uncertain output observations are represented as fuzzy belief function, and then proposes the so-called mixture data-driven T-S fuzzy model, among which, the consequents are identified by using a novel fuzzy evidential Expectation-Maximization (EM) algorithm and the antecedents are automatically constructed by using a data-driven strategy, considering both the accuracy and complexity of model. The performance of such mixture data data-driven fuzzy model was validated by conducting some unreliable sensor experiments. The numerical simulations suggest that the proposed fuzzy model can be used to approximate nonlinear systems with high accuracy when the outputs of systems are imprecisely and uncertainly observed.","PeriodicalId":397095,"journal":{"name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127557808","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: 0

Stage diagnosis for Chronic Kidney Disease based on ultrasonography 基于超声的慢性肾病分期诊断

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980889

Chi-Jim Chen, Tun-Wen Pai, H. Fujita, Chien-Hung Lee, Yang-Ting Chen, Kuo-Su Chen, Yun-Chih Chen

{"title":"Stage diagnosis for Chronic Kidney Disease based on ultrasonography","authors":"Chi-Jim Chen, Tun-Wen Pai, H. Fujita, Chien-Hung Lee, Yang-Ting Chen, Kuo-Su Chen, Yun-Chih Chen","doi":"10.1109/FSKD.2014.6980889","DOIUrl":"https://doi.org/10.1109/FSKD.2014.6980889","url":null,"abstract":"A large portion of people suffer from Chronic Kidney Disease (CKD) in the world. Unfortunately, some of them don't know they have been contracted CKD until they need dialysis treatment at the end stage. Diagnosis through non-invasive ultrasonic imaging techniques become important clinical approaches for detecting CKD, and high potential or at-risk CKD patients could avoid being infected via blood test and/or reduce chances of abrupt deterioration in renal function by taking iodinated contrast medium. This research established a detection system based on computer vision and machine learning techniques for facilitating diagnosis of CKD and different stages of CKD. Novel features and support vector machine were applied for rapid detection. In this study, several evaluations on different clustered groups were performed and compared according to estimated glomerular filtration rates (GFR). In addition, the proposed system required 0.016 seconds in average for feature extraction and classification for each testing case. The results showed that the system could produce consistent diagnosis based on noninvasive ultrasonographic approaches and which could be considered as the most proper clinical diagnosis and medical treatment for CKD patients.","PeriodicalId":397095,"journal":{"name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125954552","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: 10

Prioritization of strategies to achieve world-class manufacturing using a hybrid approach of fuzzy multiple criteria technique: Case study from Quanzhou industrial clusters 基于模糊多准则混合方法的世界级制造战略优选——以泉州产业集群为例

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980841

Qingquan Jiang, M. Safari, L. Yu, Qinglan Chen

引用次数: 1

Methods to monitor process's Spatial and temporal consumption 监控过程空间和时间消耗的方法

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980957

Huiming Jia, Rui Mao, Wenbo Wu

引用次数: 0

The application of fuzzy analysis method to the evaluation of grain production 模糊分析法在粮食生产评价中的应用

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980815

H Zhao, Qian Li, Li Li, Guanjun Zhang

引用次数: 0

Acquiring semantic relation pattern from large microblog text 从大型微博文本中获取语义关系模式

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980908

Lei Liu, Zhigang Xu, Haibo Cai, L. Diao, Shuying Yan

引用次数: 0

Abstract model of k-cloud computing k-云计算的抽象模型

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980922

Martin Bobák, L. Hluchý, V. Tran

引用次数: 3

The face detection and location system based on Zynq 基于Zynq的人脸检测定位系统

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980946

Tailin Han, Guangwen Liu, Hua Cai, Bo Wang

引用次数: 7