10th Symposium on Neural Network Applications in Electrical Engineering最新文献_第3页

Design of fuzzy controllers based on automatic selection of membership functions shapes 基于隶属函数形状自动选择的模糊控制器设计

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644090

D. Saletic, U. Popovic

引用次数: 3

Early fault detection and isolation in coal mills based on self-organizing maps 基于自组织图的煤机早期故障检测与隔离

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644054

A. Rakic

引用次数: 8

Performance of multilayer perceptrons for classification of LIBS protein spectra 多层感知器在LIBS蛋白光谱分类中的性能

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644078

D. Pokrajac, T. Vance, A. Lazarevic, A. Marcano, Y. Markushin, N. Melikechi, N. Reljin

引用次数: 14

A new method for human face recognition using texture and depth information 一种基于纹理和深度信息的人脸识别新方法

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644065

A. Assadi, A. Behrad

{"title":"A new method for human face recognition using texture and depth information","authors":"A. Assadi, A. Behrad","doi":"10.1109/NEUREL.2010.5644065","DOIUrl":"https://doi.org/10.1109/NEUREL.2010.5644065","url":null,"abstract":"The efficiency of a human face recognition system depends on the capability of face recognition in presence of different changes in the appearance of face. One of the main difficulties regarding the face recognition systems is to recognize face in different views and poses. In this paper we propose a new algorithm which utilizes the combination of texture and depth information to overcome the problem of pose variation and illumination change for face recognition. In the proposed algorithm, we first use intensity image to extract efficient key features and find probable face matches in the face database using feature matching algorithm. We have defined some criteria to find the final match based on texture information or leave the decision to second stage. In the second stage the depth information are normalized and used for pose invariant face recognition. We tested the proposed algorithm using a face database with different poses and illumination and compared the results with those of other methods. We obtained the recognition rate of 88.96 percent which shows the considerable enhancement compared to previous methods.","PeriodicalId":227890,"journal":{"name":"10th Symposium on Neural Network Applications in Electrical Engineering","volume":"186 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121727137","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

Quantum-holographic Hopfield-like biomolecular recognition 量子全息类霍普菲尔德生物分子识别

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644112

D. Raković

引用次数: 2

Mapping of sensory representation of walking and EMG of prime joint movers: Control of functional electrical stimulation 行走感觉表征的映射和主要关节运动者的肌电图:功能性电刺激的控制

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644037

I. Milovanovic, D. Popović

引用次数: 2

The database of radar echoes from various targets with spectral analysis 各种目标雷达回波数据库，并进行频谱分析

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644074

M. Andric, Boban P. Bondzulic, B. Zrnic

引用次数: 32

Classification of walking patterns in Parkinson's disease patients based on inertial sensor data 基于惯性传感器数据的帕金森病患者行走模式分类

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644040

M. Djuric-Jovicic, N. Jovičić, I. Milovanovic, S. Radovanovic, N. Kresojević, M. Popovic

引用次数: 35

Design of artificial neural network models for the prediction of the Hellenic energy consumption 希腊能耗预测的人工神经网络模型设计

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644049

P. Karampelas, V. Vita, C. Pavlatos, V. Mladenov, L. Ekonomou

{"title":"Design of artificial neural network models for the prediction of the Hellenic energy consumption","authors":"P. Karampelas, V. Vita, C. Pavlatos, V. Mladenov, L. Ekonomou","doi":"10.1109/NEUREL.2010.5644049","DOIUrl":"https://doi.org/10.1109/NEUREL.2010.5644049","url":null,"abstract":"Energy consumption predictions are essential and are required in the studies of capacity expansion, energy supply strategy, capital investment, revenue analysis and market research management. In the recent years artificial neural networks (ANN) have attracted much attention and many interesting ANN applications have been reported in power system areas, due to their computational speed, their ability to handle complex non-linear functions, robustness and great efficiency, even in cases where full information for the studied problem is absent. In this paper, several ANN models were addressed to identify the future energy consumption. Each model has been constructed using different structures, learning algorithms and transfer functions in order the best generalizing ability to be achieved. Actual input and output data were used in the training, validation and testing process. A comparison among the developed neural network models was performed in order the most suitable model to be selected. Finally the selected ANN model has been used for the prediction of the Hellenic energy consumption in the years ahead.","PeriodicalId":227890,"journal":{"name":"10th Symposium on Neural Network Applications in Electrical Engineering","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115243834","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

Automatic spleen segmentation in MRI images using a combined neural network and recursive watershed transform 结合神经网络和递归分水岭变换的MRI图像脾脏自动分割

10th Symposium on Neural Network Applications in Electrical Engineering Pub Date : 2010-11-29 DOI: 10.1109/NEUREL.2010.5644110

A. Behrad, H. Masoumi

引用次数: 16