2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)最新文献_第7页

Single node recursions in Adaptive Neuro-Fuzzy Controller 自适应神经模糊控制器中的单节点递归

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175973

P. Derugo

引用次数: 1

Database of iris images acquired in the presence of ocular pathologies and assessment of iris recognition reliability for disease-affected eyes 眼部病变的虹膜图像数据库及虹膜识别的可靠性评估

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175984

Mateusz Trokielewicz, A. Czajka, P. Maciejewicz

{"title":"Database of iris images acquired in the presence of ocular pathologies and assessment of iris recognition reliability for disease-affected eyes","authors":"Mateusz Trokielewicz, A. Czajka, P. Maciejewicz","doi":"10.1109/CYBConf.2015.7175984","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175984","url":null,"abstract":"This paper presents a database of iris images collected from disease affected eyes and an analysis related to the influence of ocular diseases on iris recognition reliability. For that purpose we have collected a database of iris images acquired for 91 different eyes during routine ophthalmology visits. This collection gathers samples for healthy eyes as well as those with various eye pathologies, including cataract, acute glaucoma, posterior and anterior synechiae, retinal detachment, rubeosis iridis, corneal vascularization, corneal grafting, iris damage and atrophy and corneal ulcers, haze or opacities. To our best knowledge this is the first database of such kind that will be made publicly available. In the analysis the data were divided into five groups of samples presenting similar anticipated impact on iris recognition: 1) healthy (no impact), 2) unaffected, clear iris (although the illness was detected), 3) geometrically distorted irides, 4) distorted iris tissue and 5) obstructed iris tissue. Three different iris recognition methods (MIRLIN, VeriEye and OSIRIS) were then used to find differences in average genuine and impostor comparison scores calculated for healthy eyes and those impacted by a disease. Specifically, we obtained significantly worse genuine comparison scores for all iris matchers and all disease-affected eyes when compared to a group of healthy eyes, what have a high potential of impacting false non-match rate.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125351178","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: 16

Linguistically motivated tied-state triphones for polish speech recognition 用于波兰语语音识别的语言驱动的固定状态三合一耳机

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175941

Piotr Żelasko, B. Ziółko, T. Jadczyk, Tomasz Pedzimaz

引用次数: 0

The model of possible Web data retrieval 可能的Web数据检索模型

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175958

Anna Bryniarska

引用次数: 5

Analysis of correlation structure of data set for efficient pattern classification 分析数据集的关联结构，实现有效的模式分类

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175901

Saptarsi Goswami, A. Chakrabarti, B. Chakraborty

{"title":"Analysis of correlation structure of data set for efficient pattern classification","authors":"Saptarsi Goswami, A. Chakrabarti, B. Chakraborty","doi":"10.1109/CYBConf.2015.7175901","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175901","url":null,"abstract":"Pattern classification or clustering plays important role in a wide variety of applications in different areas like psychology and other social sciences, biology and medical sciences, pattern recognition and data mining. A lot of algorithms for supervised or unsupervised classification have been developed so far in order to achieve high classification accuracy with lower computational cost. However, some methods or algorithms work well for some of the data sets and perform poorly on others. For any particular data set, it is difficult to find out the most suitable algorithm without some random trial and error process. It seems that the characteristics of the data set might have some influence on the algorithm for classification. In this work, the data set characteristics is studied in terms of intra attribute relationship and a measure MVS (multivariate score) has been proposed to quantify and group different data sets on the basis of the correlation structure into strong independent, weak independent, weak correlated and strong correlated data set. The performance of different feature selection algorithms on different groups of data are studied by simulation experiments with 63 publicly available bench mark data sets. It has been verified that univariate methods lead to significant performance gain for strong independent data set compared to multivariate methods while multivariate methods have better performance for strong correlated data sets.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133805028","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: 3

Simplicity or flexibility? Complementary Filter vs. EKF for orientation estimation on mobile devices 简单还是灵活?互补滤波器与EKF在移动设备上的方向估计

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175926

Michał R. Nowicki, Jan Wietrzykowski, P. Skrzypczyński

引用次数: 23

Adapting MultiBoost ensemble for class imbalanced learning 针对班级不平衡学习调整MultiBoost集成

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175899

Ghulam Mustafa, Zhendong Niu, Jie Chen

{"title":"Adapting MultiBoost ensemble for class imbalanced learning","authors":"Ghulam Mustafa, Zhendong Niu, Jie Chen","doi":"10.1109/CYBConf.2015.7175899","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175899","url":null,"abstract":"Learning with class imbalanced data sets is a challenging undertaking by the common learning algorithms. These algorithms favor majority class due to imbalanced class representation, noise and their inability to expand the boundaries of minority class in concept space. To improve the performance of minority class identification, ensembles combined with data resampling techniques have gained much popularity. However, these ensembles attain higher minority class performance at the cost of majority class performance. In this paper, we adapt the MultiBoost ensemble to deal with the minority class identification problem. Our technique inherits the power of its constituent and therefore improves the prediction performance of the minority class by expanding the concept space and overall classification performance by reducing bias and variance in the error. We compared our technique with seven existing simple and ensemble techniques using thirteen data sets. The experimental results show that proposed technique gains significant performance improvement on all tested metrics. Furthermore, it also has inherited advantage over other ensembles due to its capability of parallel computation.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134520577","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

Online platform to support business analysis and Process Optimization in transportation organizations 在线平台，支持运输组织的业务分析和流程优化

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175959

G. Kolaczek, P. Swiatek, A. Grzech, K. Juszczyszyn, Pawel Stelmach, Lukasz Falas, Arkadiusz Slawek, Patryk Schauer

引用次数: 0

Content-based image retrieval using local texture-based color histogram 基于局部纹理的颜色直方图的基于内容的图像检索

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175967

Bingfei Nan, Ye Xu, Zhichun Mu, Long Chen

引用次数: 11

Holistic integration of enactive entities into cyber physical systems 将活动实体整体集成到网络物理系统中

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175947

B. Hadorn, M. Courant, B. Hirsbrunner

引用次数: 8