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

Combining nearest neighbour classifiers based on small subsamples for big data analytics 结合基于小子样本的最近邻分类器进行大数据分析

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175952

B. Krawczyk, Michal Wozniak

{"title":"Combining nearest neighbour classifiers based on small subsamples for big data analytics","authors":"B. Krawczyk, Michal Wozniak","doi":"10.1109/CYBConf.2015.7175952","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175952","url":null,"abstract":"Contemporary machine learning systems must be able to deal with ever-growing volumes of data. However, most of the canonical classifiers are not well-suited for big data analytics. This is especially vivid in case of distance-based classifiers, where their classification time is prohibitive. Recently, many methods for adapting nearest neighbour classifier for big data were proposed. We investigate simple, yet efficient technique based on random under-sampling of the dataset. As we deal with stationary data, one may assume that a subset of objects will sufficiently capture the properties of given dataset. We propose to build distance-based classifiers on the basis of very small subsamples and then combine them into an ensemble. With this, one does not need to aggregate datasets, only local decisions of classifiers. On the basis of experimental results we show that such an approach can return comparable results to nearest neighbour classifier over the entire dataset, but with a significantly reduced classification time. We investigate the number of sub-samples (ensemble members), that are required for capturing the properties of each dataset. Finally, we propose to apply our sub-sampling based ensemble in a distributed environment, which allows for a further reduction of the computational complexity of nearest neighbour rule for big data.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"32 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":"127064253","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

Set of experience and decisional DNA: Toward brains for cyber-physical systems and industry of the future 一套经验和决策DNA:走向未来网络物理系统和工业的大脑

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175898

E. Szczerbicki, C. Sanín, S. Shafiq

引用次数: 2

Design and development of a lightweight multi-UAV simulator 轻型多无人机模拟器的设计与开发

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175942

V. Rodríguez-Fernández, Héctor D. Menéndez, David Camacho

引用次数: 25

Balancing throughput and latency for an aerial robot over a wireless secure communication link 在无线安全通信链路上平衡空中机器人的吞吐量和延迟

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175929

R. D. Sparrow, A. A. Adekunle, R. J. Berry, R. Farnish

引用次数: 4

Study on time-dependent departure process in a finite-buffer queueing model with BMAP-type input stream 具有bmap型输入流的有限缓冲排队模型中随时间变化的出发过程研究

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175940

W. Kempa

引用次数: 3

Swarm intelligence applied to identification of nonlinear ship steering model 将群智能应用于非线性船舶转向模型辨识

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175920

M. Tomera

引用次数: 12

Printed steganography applied for the authentication of identity photos in face verification 印刷隐写术应用于人脸验证中身份照片的认证

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175987

Włodzimierz Kasprzak, M. Stefanczyk, A. Wilkowski

引用次数: 2

Application of an internal model Speed Control for PMSM with variable mechanical paremeters 内模速度控制在变机械参数永磁同步电机中的应用

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBCONF.2015.7175970

Pajchrowski Tomasz

引用次数: 3

Indoor microlocation with BLE beacons and incremental rule learning 使用BLE信标和增量规则学习的室内微定位

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175912

Szymon Bobek, Olgierd Grodzki, G. J. Nalepa

引用次数: 14

Join Gabor and scattering transform for urine sediment particle texture analysis 结合Gabor和散射变换进行尿液沉积物颗粒纹理分析

2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175969

Chunli Li, Yuanyan Tang, Huiwu Luo, Xianwei Zheng

{"title":"Join Gabor and scattering transform for urine sediment particle texture analysis","authors":"Chunli Li, Yuanyan Tang, Huiwu Luo, Xianwei Zheng","doi":"10.1109/CYBConf.2015.7175969","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175969","url":null,"abstract":"There are many kinds of corporeal ingredients in urinary sediment which must be identified to confirm the diagnosis of an abnormality. In this paper, we refine a method which integrates both Gabor filter and scattering transform for texture analysis in urinary sediment images. The proposed scheme is based on the conventional Gabor filter and the recently developed scattering transform. The Gabor filter bank has the ability to capture the filtering responses according to the scale and orientation of texture. Besides, the scattering transformation provides a distinctive property of robust description, which is invariant to rotations and stable to spatial deformation. The excellent representation of Gabor filter and scattering transform has been severally studied in recent work, yet they have not been used in urinary sediment images. In this work, we propose to use both Gabor filter and scattering transformation to extract the texture feature of urinary sediment images. Coupling with an efficient support vector machine (SVM) classifier, the proposed scheme tends to shown superiority as compared to other single descriptive alternatives in real urinary sediment experiments.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"1018 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":"123117655","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: 8