2015 Federated Conference on Computer Science and Information Systems (FedCSIS)最新文献_第9页

Simulation and formal modelling of yaw control in a drive-by-wire application 线控驱动系统偏航控制的仿真与形式化建模

2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Pub Date : 2015-10-11 DOI: 10.15439/2015F132

R. Banach, P. V. Schaik, E. Verhulst

引用次数: 8

Pedestrian tracking in video sequences: A particle filtering approach 视频序列中的行人跟踪:粒子滤波方法

2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Pub Date : 2015-10-11 DOI: 10.15439/2015F158

Mateusz Owczarek, P. Baranski, P. Strumiłło

{"title":"Pedestrian tracking in video sequences: A particle filtering approach","authors":"Mateusz Owczarek, P. Baranski, P. Strumiłło","doi":"10.15439/2015F158","DOIUrl":"https://doi.org/10.15439/2015F158","url":null,"abstract":"In this work we study the methods for pedestrian tracking in video sequences and indicate various applications of these methods ranging from surveillance systems to aiding the visually impaired persons. First, we define the general problem of object tracking that comprises the tasks of object detection, identifying the flow of object location in consecutive video images and finally analysis of the tracked trajectory data. We review the well known object tracking techniques i.e. the Mean-Shift and the CAMSHIFT algorithm and discuss their properties. Then we introduce the computational technique known as particle filtering (PF) and explain how we have applied it to the tasks of pedestrian tracking. We compare the PF approach against the Mean-Shift and the CAMSHIFT algorithms in terms of tracking robustness and the required computational demand. We conclude, that on the tested video sequences, the PF tracker outperforms the Mean-Shift and by a small margin the CAMSHIFT algorithm. The PF tracker requires more computational power, however, its tracking performance can be flexibly adjusted to the application requirements.","PeriodicalId":276884,"journal":{"name":"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129265750","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: 7

InterCriteria Analysis of crossover and mutation rates relations in simple genetic algorithm 简单遗传算法中交叉率和突变率关系的标准间分析

2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Pub Date : 2015-10-11 DOI: 10.15439/2015F178

M. Angelova, O. Roeva, T. Pencheva

引用次数: 36

Trigger based on the artificial neural network implemented in the cyclone V FPGA for a detection of neutrino-origin showers in the Pierre Auger surface detector 基于人工神经网络的触发器在旋风V FPGA中实现，用于探测皮埃尔俄歇表面探测器中的中微子源阵雨

2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Pub Date : 2015-10-11 DOI: 10.15439/2015F208

Z. Szadkowski, K. Pytel

引用次数: 2

Genetic algorithms for balanced spanning tree problem 平衡生成树问题的遗传算法

2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Pub Date : 2015-10-11 DOI: 10.15439/2015F249

Riham Moharam, E. Morsy, Ismail A. Ismail

引用次数: 4

Comparison of SVM and k-NN classifiers in the estimation of the state of the arteriovenous fistula problem SVM与k-NN分类器在动静脉瘘状态估计中的比较

2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Pub Date : 2015-10-11 DOI: 10.15439/2015F194

Marcin Grochowina, L. Leniowska

引用次数: 7

Transformation of nominal features into numeric in supervised multi-class problems based on the weight of evidence parameter 基于证据参数权重的有监督多类问题标称特征的数值化

2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Pub Date : 2015-10-11 DOI: 10.15439/2015F90

Eftim Zdravevski, Petre Lameski, A. Kulakov, S. Kalajdziski

{"title":"Transformation of nominal features into numeric in supervised multi-class problems based on the weight of evidence parameter","authors":"Eftim Zdravevski, Petre Lameski, A. Kulakov, S. Kalajdziski","doi":"10.15439/2015F90","DOIUrl":"https://doi.org/10.15439/2015F90","url":null,"abstract":"Machine learning has received increased interest by both the scientific community and the industry. Most of the machine learning algorithms rely on certain distance metrics that can only be applied to numeric data. This becomes a problem in complex datasets that contain heterogeneous data consisted of numeric and nominal (i.e. categorical) features. Thus the need of transformation from nominal to numeric data. Weight of evidence (WoE) is one of the parameters that can be used for transformation of the nominal features to numeric. In this paper we describe a method that uses WoE to transform the features. Although the applicability of this method is researched to some extent, in this paper we extend its applicability for multi-class problems, which is a novelty. We compared it with the method that generates dummy features. We test both methods on binary and multi-class classification problems with different machine learning algorithms. Our experiments show that the WoE based transformation generates smaller number of features compared to the technique based on generation of dummy features while also improving the classification accuracy, reducing memory complexity and shortening the execution time. Be that as it may, we also point out some of its weaknesses and make some recommendations when to use the method based on dummy features generation instead.","PeriodicalId":276884,"journal":{"name":"2015 Federated Conference on Computer Science and Information Systems (FedCSIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132252995","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: 20

Segmentation of cerebrospinal fluid from 3D CT brain scans using modified Fuzzy C-Means based on super-voxels 基于超体素的改进模糊c均值分割3D CT脑扫描脑脊液

2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Pub Date : 2015-10-11 DOI: 10.15439/2015F154

Abdelkhalek Bakkari, A. Fabijańska

引用次数: 4

Management of requirements for the projects of the diagnostic systems 诊断系统项目的需求管理

2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Pub Date : 2015-10-11 DOI: 10.15439/2015F175

M. Amarowicz

引用次数: 2

Research proposal: Barriers to new user and new domain adoption of the XSEDE cyberinfrastructure 研究建议:新用户和新领域采用XSEDE网络基础设施的障碍

2015 Federated Conference on Computer Science and Information Systems (FedCSIS) Pub Date : 2015-10-11 DOI: 10.15439/2015F244

R. Knepper

引用次数: 0