2015 Intelligent Systems and Computer Vision (ISCV)最新文献_第4页

Preprocessing phase for initializing the PRSOM architecture 初始化PRSOM架构的预处理阶段

2015 Intelligent Systems and Computer Vision (ISCV) Pub Date : 2015-03-25 DOI: 10.1109/ISACV.2015.7106190

Harchli Fidae, En-naimani Zakariae, Es-Safi Abdelatif, Ettaouil Mohamed

{"title":"Preprocessing phase for initializing the PRSOM architecture","authors":"Harchli Fidae, En-naimani Zakariae, Es-Safi Abdelatif, Ettaouil Mohamed","doi":"10.1109/ISACV.2015.7106190","DOIUrl":"https://doi.org/10.1109/ISACV.2015.7106190","url":null,"abstract":"The self-organizing map (SOM) is a popular neural network which was designed for solving problems that involve tasks such as clustering and visualization. Specially, It provides a new strategy of clustering using a competition and co-operation principal. The probabilistic Kohonen network (PRSOM) is the stochastic version of classical one. However, determination of the optimal number of neurons and their initial weight vectors in the map is still a big problem in the literature. These parameters have a great impact on the learning process of the network, the convergence and the quality of results. Also determination of clusters' number of datasets is a very difficult task. In this paper we extend the original Kohonen network to classify unlabeled data and determine the number of clusters. The task consists of generating a heuristic method before the learning phase of the network. The main goal of this method is looking for the initial parameters of the map. We compare the result of the proposed method with that of the original Kohonen network. We further experiment the applicability and the performance of the method on dataset Iris. The result shows that the proposed method is able to produce satisfactory clustering results.","PeriodicalId":426557,"journal":{"name":"2015 Intelligent Systems and Computer Vision (ISCV)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121440622","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

Comparative study between different bases of transformation for compressive sensing of images 图像压缩感知中不同变换基的比较研究

2015 Intelligent Systems and Computer Vision (ISCV) Pub Date : 2015-03-25 DOI: 10.1109/ISACV.2015.7106194

Youssef Mourchid, M. El Hassouni

引用次数: 2

New model for aircraft landing scheduling using real time algorithms scheduling 基于实时调度算法的飞机着陆调度新模型

2015 Intelligent Systems and Computer Vision (ISCV) Pub Date : 2015-03-25 DOI: 10.1109/ISACV.2015.7105535

S. Chougdali, Asmaa Roudane, K. Mansouri, M. Youssfi, Mohammed Qbadou

引用次数: 6

Maximum power point tracking for a photovoltaic water pumping system with sliding mode control and fuzzy wavelet network 基于滑模控制和模糊小波网络的光伏水泵系统最大功率点跟踪

2015 Intelligent Systems and Computer Vision (ISCV) Pub Date : 2015-03-25 DOI: 10.1109/ISACV.2015.7106183

Bouchra Sefriti, O. Dahhani, I. Boumhidi

引用次数: 2

Toward an effective hybrid collaborative filtering: A new approach based on matrix factorization and heuristic-based neighborhood 一种基于矩阵分解和启发式邻域的有效混合协同过滤方法

2015 Intelligent Systems and Computer Vision (ISCV) Pub Date : 2015-03-25 DOI: 10.1109/ISACV.2015.7105543

Yasser El Madani El Alami, E. Nfaoui, Omar El Beqqali

{"title":"Toward an effective hybrid collaborative filtering: A new approach based on matrix factorization and heuristic-based neighborhood","authors":"Yasser El Madani El Alami, E. Nfaoui, Omar El Beqqali","doi":"10.1109/ISACV.2015.7105543","DOIUrl":"https://doi.org/10.1109/ISACV.2015.7105543","url":null,"abstract":"“Collaborative filtering” (CF) methods provide a good solution for recommendation systems. Neighborhood formation is considered as the main phase in memory approaches. Unfortunately, this phase encounters many problems such as sparsity and scalability, especially for huge datasets which consists of a large number of users and items. This paper presents a new hybrid approach for collaborative filtering. It is based on two heuristic approaches for neighborhood selection. The first of which is based on selecting users who rated the same items as the active user called “intersection neighborhood”, while the second one builds the neighborhood using all users who rated one item at least as the active user called “union neighborhood”. In addition, we employ matrix factorization technique to learn the latent characteristics of the selected neighborhood (users or items) in order to quickly predict good quality of the unknown ratings. Finally, experiments show that the proposed approaches give more predictions accuracy than the traditional collaborative filtering.","PeriodicalId":426557,"journal":{"name":"2015 Intelligent Systems and Computer Vision (ISCV)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131525839","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: 6

Optimal design of second generation current conveyors by the Artificial Bee Colony technique 基于人工蜂群技术的第二代传送带优化设计

2015 Intelligent Systems and Computer Vision (ISCV) Pub Date : 2015-03-25 DOI: 10.1109/ISACV.2015.7106172

B. Benhala, Hamid Bouyghf, A. Lachhab, B. Bouchikhi

引用次数: 15

Enhancement of 3D reconstruction process in terms of beautification and efficiency using geometric constraints 利用几何约束增强三维重建过程的美化和效率

2015 Intelligent Systems and Computer Vision (ISCV) Pub Date : 2015-03-25 DOI: 10.1109/ISACV.2015.7106180

Afafe Annich, A. El Abderrahmani, K. Satori

{"title":"Enhancement of 3D reconstruction process in terms of beautification and efficiency using geometric constraints","authors":"Afafe Annich, A. El Abderrahmani, K. Satori","doi":"10.1109/ISACV.2015.7106180","DOIUrl":"https://doi.org/10.1109/ISACV.2015.7106180","url":null,"abstract":"In this paper, we present a 3D reconstruction approach from uncalibrated views using geometric constraints. Basically speaking, we used bundle adjustment based on Levenberg-Marquardt optimization with the aim to estimate our 3D scene. In fact, it is different to the classic case. We integrate a pose estimation algorithm in 3D reconstruction process. As it is known, Levenberg-Marquardt algorithm presents low convergence rate 0% if initial values are wrong. The use of pose estimation previously cited can improve convergence but, it is still not satisfactory for users. So, using geometric constraints present a good solution. It brings us many advantages; it helps us to reduce estimated parameters number and stabilizes good quality for 3D results. In fact, we should recall that we use uncalibrated views, so we don't have any prior information about our 3D scene to achieve 3D reconstruction with no pertinent initial values used in Levenberg-Marquardt algorithm. In this present work, we try as much as possible through a comparative analysis to proof the importance of geometric constraints use in 3D reconstruction in terms of results reliability, process speed and convergence rate. Several data will be used in the purpose to demonstrate the efficiency of our present approach using geometric constraints.","PeriodicalId":426557,"journal":{"name":"2015 Intelligent Systems and Computer Vision (ISCV)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132409536","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: 5

A robust intelligent control for a variable speed wind turbine based on general regression neural network 基于广义回归神经网络的变转速风力机鲁棒智能控制

2015 Intelligent Systems and Computer Vision (ISCV) Pub Date : 2015-03-25 DOI: 10.1109/ISACV.2015.7106174

El-mahjoub Boufounas, Youssef Berrada, Miloud Koumir, I. Boumhidi

{"title":"A robust intelligent control for a variable speed wind turbine based on general regression neural network","authors":"El-mahjoub Boufounas, Youssef Berrada, Miloud Koumir, I. Boumhidi","doi":"10.1109/ISACV.2015.7106174","DOIUrl":"https://doi.org/10.1109/ISACV.2015.7106174","url":null,"abstract":"In this paper, a robust general regression neural network sliding mode (GRNNSM) controller is designed for a variable speed wind turbine. The objective of the proposed control is defined in relation with the trade-off between the wind energy conversion maximization and the minimization of the stress on the drive train shafts. Sliding mode control approach (SMC) emerges as an especially suitable option to deal with variable speed wind turbine. However, for large uncertain systems, the SMC produces chattering problems due to the higher needed switching gain. In order to reduce this gain, general regression neural network (GRNN) is used for the prediction of model unknown component and hence enable a lower switching gain to be used. In the present work, back-propagation (BP) algorithm will be used to train online the GRNN weights. A robust control term with low switching gain is added to compensate the neural network errors. The stability is shown by the Lyapunov theory and the control action used did not exhibit any chattering behavior. The effectiveness of the designed method is illustrated in simulations by the comparison with traditional SMC.","PeriodicalId":426557,"journal":{"name":"2015 Intelligent Systems and Computer Vision (ISCV)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134422480","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: 4

Comparative study and improvement of acoustic vectors extractors: Multiple streams applied to the recognition of Arabic numerals 声学矢量提取器的比较研究与改进:多流应用于阿拉伯数字识别

2015 Intelligent Systems and Computer Vision (ISCV) Pub Date : 2015-03-25 DOI: 10.1109/ISACV.2015.7106179

Abdelmajid Lamkadam, M. Karim

引用次数: 1

Towards reputation measurement in online social networks 在线社交网络中的声誉测量研究

2015 Intelligent Systems and Computer Vision (ISCV) Pub Date : 2015-03-25 DOI: 10.1109/ISACV.2015.7105540

M. El Marrakchi, M. Bellafkih, Hicham Bensaid

引用次数: 7