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Titlebook: Neural Nets and Surroundings; 22nd Italian Worksho Bruno Apolloni,Simone Bassis,Francesco Carlo Morab Book 2013 Springer-Verlag Berlin Heid

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发表于 2025-3-21 17:33:03 | 显示全部楼层 |阅读模式
书目名称Neural Nets and Surroundings
副标题22nd Italian Worksho
编辑Bruno Apolloni,Simone Bassis,Francesco Carlo Morab
视频video
概述Recent research in neural networks.Results of 21th Italian Workshop on Neural Networks (WIRN2012)held June 3-5, Vietri sul Mare, Salerno, Italy.Written by leading experts in the field
丛书名称Smart Innovation, Systems and Technologies
图书封面Titlebook: Neural Nets and Surroundings; 22nd Italian Worksho Bruno Apolloni,Simone Bassis,Francesco Carlo Morab Book 2013 Springer-Verlag Berlin Heid
描述.This volume collects a selection of contributions which has been presented at the 22nd Italian Workshop on Neural Networks, the yearly meeting of the Italian Society for Neural Networks (SIREN). The conference was held in Italy, Vietri sul Mare (Salerno), during May 17-19, 2012. The annual meeting of SIREN is sponsored by International Neural Network Society (INNS), European Neural Network Society (ENNS) and IEEE Computational Intelligence Society (CIS). The book – as well as the workshop-  is organized in three main components, two special sessions and a group of regular sessions featuring different aspects and point of views of artificial neural networks and natural intelligence, also including applications of present compelling interest..
出版日期Book 2013
关键词Artificial Intelligence; Computational Intelligence; Intelligent Systems; Neural Networks
版次1
doihttps://doi.org/10.1007/978-3-642-35467-0
isbn_softcover978-3-642-44132-5
isbn_ebook978-3-642-35467-0Series ISSN 2190-3018 Series E-ISSN 2190-3026
issn_series 2190-3018
copyrightSpringer-Verlag Berlin Heidelberg 2013
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Control of Coffee Grinding with General Regression Neural Networks work, a general regression neural network approach is used to learn to control two grinders used for coffee production at LAVAZZA factory, obtaining average control error of the order of a few .m. The results appear promising for the future development of an automatic decision support system.
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Defects Detection in Pistachio Nuts Using Artificial Neural Networks from the positive samples. A functional-link neural network is then used for the proper classification task. By means of a repeated cross-validation, the proposed solution showed a correct recognition rate of 99.6%, with a false positive rate of 0.3% with a single classifier and 0.1% with a combined one.
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Measures of Brain Connectivity through Permutation Entropy in Epileptic Disorderst electrodes placed over the scalp, in order to simulate the network phenomena that occur in the brain. This technique was tested over two EEG recordings: a healthy subject and an epileptic subject affected by absence seizures.
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A New System for Automatic Recognition of Italian Sign Languages-validation method on the Italian Sign Language Database A3LIS-147, maintaining the orthogonality between training and test sets. The obtained recognition accuracy averaged across all signers is 47.24%, which represents an encouraging result and demonstrates the effectiveness of the idea.
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Artificial Neural Network (ANN) Morphological Classification of Magnetic Resonance Imaging in Multipumber of images. We can observe that the percentage of correct results on 21 images (93.81%) increased if compared to the study performed on 13 images (92.31%). This methodology could be used to monitor evolution in time of lesions of each patient and to correlate this to MS phases (i.e. to know if the lesions change their form).
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Neural Moving Object Detection by Pan-Tilt-Zoom Camerasobject detection in image sequences taken from PTZ cameras, we present a neural-based background subtraction approach where the background model automatically adapts in a self-organizing way to changes in the scene background. Experiments conducted on real image sequences demonstrate the effectiveness of the presented approach.
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