The 2012 International Joint Conference on Neural Networks (IJCNN)最新文献_第9页

Biasing the overlapping and non-overlapping sub-windows of EEG recording 脑电记录重叠和非重叠子窗口的偏置

The 2012 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2012-06-10 DOI: 10.1109/IJCNN.2012.6252465

A. Atyabi, S. Fitzgibbon, D. Powers

{"title":"Biasing the overlapping and non-overlapping sub-windows of EEG recording","authors":"A. Atyabi, S. Fitzgibbon, D. Powers","doi":"10.1109/IJCNN.2012.6252465","DOIUrl":"https://doi.org/10.1109/IJCNN.2012.6252465","url":null,"abstract":"EEG recording involves having subjects sit on a chair for a couple of hours without being allowed to move and being asked to repeatedly perform various mental, computational, motor imaginary or any other tasks for some specific amount of time. This is a time consuming, boring and complicated procedure during which there is no guarantee that the subject will maintain the proper level of concentration on the requested task at all times, this is apart from the possible muscle activity that might be accidentally generated. This might cause complications in terms of generating signals that do not necessarily contain useful information for classification in the whole tasks time duration. This effect is more likely to appear on recordings in which the task period is longer than usual as in the dataset IVa from BCI competition III in which the task time duration is set to 3.5s. This study investigate the impact of various fragments of time on classification performance. The idea is to improve the classification performance by providing higher concentration on segments of the signal that we assume the subject had better concentration on the task. The results indicate the importance of the middle and end sub-epochs while it illustrate lower performance during the earlier sub-windows.","PeriodicalId":287844,"journal":{"name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131249292","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: 9

Relevance learning for short high-dimensional time series in the life sciences 生命科学中短高维时间序列的相关学习

The 2012 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2012-06-10 DOI: 10.1109/IJCNN.2012.6252653

Frank-Michael Schleif, A. Gisbrecht, B. Hammer

{"title":"Relevance learning for short high-dimensional time series in the life sciences","authors":"Frank-Michael Schleif, A. Gisbrecht, B. Hammer","doi":"10.1109/IJCNN.2012.6252653","DOIUrl":"https://doi.org/10.1109/IJCNN.2012.6252653","url":null,"abstract":"Digital data characterizing physiological processes over time are becoming increasingly important such as spectrometric data or gene expression profiles. Typical characteristics of such data are high dimensionality due to a fine grained measurement, but usually only few time points of the series. Due to the short length, classical time series models cannot be used. At the same time, due to the high dimensionality, data cannot be treated by means of time windows using simple vectorial techniques. Here, we consider the generative topographic mapping through time (GTM-TT) as a highly regularized model for time series inspection in the unsupervised setting, based on hidden Markov models enhanced with topographic mapping facilities. We extend the model such that supervised classification can be built on top of GTM-TT, resulting in supervised GTM-TT, and we extend the technique by supervised relevance learning. The latter adapts the metric according to given auxiliary information resulting in an interpretable form which can deal with high dimensional inputs. We demonstrate the technique in simulated data as well as an example from the biomedical domain, reaching state of the art classification accuracy in both cases.","PeriodicalId":287844,"journal":{"name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131314150","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: 2

Sequential causal estimation and learning from time-varying images 时序因果估计与时变图像学习

The 2012 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2012-06-10 DOI: 10.1109/IJCNN.2012.6252480

R. Chalasani, Goktug T. Cinar, J. Príncipe

引用次数: 0

Fast predictive inverse neurocontrol: Comparative simulation and experiment 快速预测逆神经控制:比较仿真与实验

The 2012 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2012-06-10 DOI: 10.1109/IJCNN.2012.6252567

K. Zmeu, B. S. Notkin, P. Dyachenko, V. Kovalev

引用次数: 6

Support vector machines for program analysis 支持向量机的程序分析

The 2012 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2012-06-10 DOI: 10.1109/IJCNN.2012.6252469

Andrea Flexeder, Matthias Putz, T. Runkler

引用次数: 0

Color reproduction by means of a Compactly Supported Radial Basis Function space mapping 用紧支持径向基函数空间映射的方法再现色彩

The 2012 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2012-06-10 DOI: 10.1109/IJCNN.2012.6252420

Ladys Rodriguez, L. Diago, I. Hagiwara, F. Magoulès

{"title":"Color reproduction by means of a Compactly Supported Radial Basis Function space mapping","authors":"Ladys Rodriguez, L. Diago, I. Hagiwara, F. Magoulès","doi":"10.1109/IJCNN.2012.6252420","DOIUrl":"https://doi.org/10.1109/IJCNN.2012.6252420","url":null,"abstract":"Colors play an important role for customers to find their preference. The perception of the color depends on the devices used to show the colors and it changes with the color transformation between one device and another. This paper proposes an iterative approach for color reproduction of industrial manufacturer samples in a commercial printer device using a Compactly-Supported Radial Basis Functions (CSRBF) space mapping which avoids unnecessary printings during color reproduction. In order to illustrate an application of the proposed color reproduction, four users manually adjusted 28 samples of colors provided by painting manufacturers. The 28 samples are automatically reproduced with good accuracy according to the International Commission on Illumination (CIE) color difference formula using the proposed CSRBF-based iterative reproduction approach. The proposed CSRBF-based approach is compared with a related Artificial Neural Network (ANN) mapping. Proposed CSRBF mapping reproduced the 100% of the colors within a threshold for industrial process taking only 3.1 sec, while the ANN mapping only reproduced the 78.57% of the colors in much time (60.1 sec).","PeriodicalId":287844,"journal":{"name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121339587","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

A statistical aimbot detection method for online FPS games 一种在线FPS游戏的统计目标机器人检测方法

The 2012 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2012-06-10 DOI: 10.1109/IJCNN.2012.6252489

Su-Yang Yu, Nils Y. Hammerla, Jeff Yan, Péter András

{"title":"A statistical aimbot detection method for online FPS games","authors":"Su-Yang Yu, Nils Y. Hammerla, Jeff Yan, Péter András","doi":"10.1109/IJCNN.2012.6252489","DOIUrl":"https://doi.org/10.1109/IJCNN.2012.6252489","url":null,"abstract":"First Person Shooter (FPS) is a popular genre in online gaming, unfortunately not everyone plays the game fairly, and this hinders the growth of the industry. The aiming robot (aimbot) is a common cheating mechanism employed in this genre, it differs from many other common online bots in that there is a human operating alongside the bot, and thus the in-game data exhibit both human and bot-like behaviour. The aimbot users can aim much better than the average player. However, there are also a large number of highly skilled players who can aim much better than the average player, some of these players have in the past been banned from servers due to false accusations from their peers. Therefore, it would be interesting to find out if and where the honest player's and the bot user's behaviour differ. In this paper we investigate the difference between the aiming abilities of aimbot users and honest human players. We introduce two novel features and have conducted an experiment using a modified open source FPS game. Our data shows that there is significant difference between behaviours of honest players and aimbot users. We propose a voting scheme to improve aimbot detection in FPS based on distribution matching, and have achieved approximately 93% in both True positive and True negative rates with one of our features.","PeriodicalId":287844,"journal":{"name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121604938","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: 14

On robust biometric identity verification via sparse encoding of faces: Holistic vs local approaches 基于人脸稀疏编码的鲁棒生物特征身份验证:整体与局部方法

The 2012 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2012-06-10 DOI: 10.1109/IJCNN.2012.6252611

Yongkang Wong, M. Harandi, Conrad Sanderson, B. Lovell

{"title":"On robust biometric identity verification via sparse encoding of faces: Holistic vs local approaches","authors":"Yongkang Wong, M. Harandi, Conrad Sanderson, B. Lovell","doi":"10.1109/IJCNN.2012.6252611","DOIUrl":"https://doi.org/10.1109/IJCNN.2012.6252611","url":null,"abstract":"In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the related literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in identification is that the gallery always has sufficient samples per subject to linearly reconstruct a query image. Unfortunately, such assumption is easily violated in the more challenging and realistic face verification scenario. A verification algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person, while explicitly taking into account the possibility of impostor attacks. In this paper, we first discuss why most of the SR literature is not applicable to verification problems. Motivated by the success of bag-of-words methods in the field of object recognition, which describe an image as a set of local patches or interest points, we then propose to tackle the verification problem by encoding each local face patch through SR. The locally encoded sparse vectors are pooled to form regional descriptors, where each descriptor covers a relatively large portion of the face. Experiments in various challenging conditions show that the proposed method achieves high and robust verification performance.","PeriodicalId":287844,"journal":{"name":"The 2012 International Joint Conference on Neural Networks (IJCNN)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126318968","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: 22

Growing Self-organizing Trees for knowledge discovery from data 从数据中发现知识的自组织树

The 2012 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2012-06-10 DOI: 10.1109/IJCNN.2012.6252396

Nhat-Quang Doan, Hanene Azzag, M. Lebbah

引用次数: 2

Offline handwritten signature verification through network radial basis functions optimized by Differential Evolution 基于差分进化优化网络径向基函数的离线手写签名验证

The 2012 International Joint Conference on Neural Networks (IJCNN) Pub Date : 2012-06-10 DOI: 10.1109/IJCNN.2012.6252720

Saulo Henrique Leoncio de Medeiros Napoles, C. Zanchettin

引用次数: 7