2008 4th International IEEE Conference Intelligent Systems最新文献_第6页

Multi-valued logical method for knowledge extraction and updating in real time 基于多值逻辑的知识提取与实时更新方法

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670545

E. Gegov, B. Vatchova, E. Gegov

引用次数: 3

A fast approach to novelty detection in video streams using recursive density estimation 基于递归密度估计的视频流新颖性快速检测方法

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670523

R. Ramezani, P. Angelov, Xiaowei Zhou

{"title":"A fast approach to novelty detection in video streams using recursive density estimation","authors":"R. Ramezani, P. Angelov, Xiaowei Zhou","doi":"10.1109/IS.2008.4670523","DOIUrl":"https://doi.org/10.1109/IS.2008.4670523","url":null,"abstract":"Video-based surveillance and security become extremely important in the new, 21st century for human safety, counter-terrorism, traffic control etc. Visual novelty detection and tracking are key elements of such activities. The current state-of-the-art approaches often suffer from high computational, memory storage costs and from not being fully automated (they usually require a human operator in the loop). This paper introduces a new approach to the problem of novelty detection in video streams that is based on recursive, and therefore, computationally efficient density estimation by a Cauchy type of kernel (as opposed to the usually used Gaussian one). The idea of the proposed approach stems from the recently introduced evolving clustering approach, eClustering and is suitable for online and real-time applications in fully autonomous and unsupervised systems as a stand-alone novelty detector or for priming a tracking algorithm. The approach proposed in this paper has evolving property - it can gradually update the background model and the criteria to detect novelty by unsupervised online learning. The proposed approach is faster by an order of magnitude than the well known kernel density estimation (KDE) method for background subtraction, while having has adaptive characteristics, and does not need any threshold to be pre-specified. Recursive expressions similar to the proposed approach in this paper can also be applied to image segmentation and landmark recognition used for self-localization in robotics. If combined with a real-time prediction using Kalman filter or evolving Takagi-Sugeno fuzzy models a fast and fully autonomous tracking system can be realized with potential applications in surveillance and robotic systems.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116525624","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: 38

Learning in networks: Complex-valued neurons, pruning, and rule extraction 网络中的学习:复值神经元、剪枝和规则提取

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670394

J. Zurada, I. Aizenberg, M. Mazurowski

引用次数: 3

A case-based planning approach to design and plan ITMAS 一个基于案例的规划方法来设计和规划ITMAS

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670479

S. Saberi, Esfandiar Mohammad

引用次数: 0

Genetic Algorithm approach for Optimal Power Flow with FACTS devices 具有FACTS器件的最优潮流遗传算法

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670477

R. Banu, D. Devaraj

引用次数: 22

Neural network application in strange attractor investigation to detect a FGD 神经网络在奇异吸引子检测中的应用

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670470

Y. Z. Mehran, A. Nasrabadi

引用次数: 1

Neural network - based estimation of reaction rates with partly unknown states and completely known kinetics coefficients 基于神经网络的部分未知状态和完全已知动力学系数的反应速率估计

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670443

P. Georgieva, S. de Azevedo

引用次数: 0

Optimizing occlusion appearances in 3D association rules visualization 三维关联规则可视化中遮挡现象的优化

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670537

Olivier Couturier, Vincent Dubois, Tien-Ning Hsu, E. Nguifo

引用次数: 7

Intelligent component based batch control using IEC61499 and ANSI/ISA S88 基于智能组件的批量控制使用IEC61499和ANSI/ISA S88

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670424

D. Ivanova, Georg Frey, I. Batchkova

引用次数: 9

Optimal decompositions of matrices with grades 带等级矩阵的最优分解

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670530

R. Belohlávek

{"title":"Optimal decompositions of matrices with grades","authors":"R. Belohlávek","doi":"10.1109/IS.2008.4670530","DOIUrl":"https://doi.org/10.1109/IS.2008.4670530","url":null,"abstract":"We present theoretical results regarding decomposition of matrices with grades, i.e. matrices I with entries from a bounded ordered set L such as the real unit interval [0, 1]. If I is such an n times m matrix, we look for a decomposition of I into a product A omicron B of an ntimesk matrix A and a ktimesm matrix B with entries from L with k as small as possible. This problem generalizes the decomposition problem of Boolean factor analysis which is a particular case when L has just two elements 0 and 1. The product we consider is a supt-norm product of which the well known max-min product of Boolean matrices as well as max-min and max-min product of matrices with entries from [0, 1] are particular examples. I, A, and B can be interpreted as object times attribute, object times factor, and factor times attribute matrices describing degrees of expression of attributes on objects, factors on objects, and attributes on factors. In this interpretation, a decomposition I into A omicron B corresponds to discovery of k factors explaining the original data I. We propose to use formal concepts of I in the sense of formal concept analysis as factors. The formal concepts are fixed points of a particular closure operator and can be seen as particular submatrices of I. We prove several results regarding such a decomposition including a theorem which says that decompositions using formal concepts as factors are optimal in that they provide us with the least number of factors possible. Based on the geometrical insight provided by the theorem, we propose a greedy approximation algorithm for finding optimal decompositions. We provide examples illustrating the concepts and implications of the results.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121443737","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: 12