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Titlebook: Neural Information Processing; 19th International C Tingwen Huang,Zhigang Zeng,Chi Sing Leung Conference proceedings 2012 Springer-Verlag B

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发表于 2025-3-21 16:41:05 | 显示全部楼层 |阅读模式
书目名称Neural Information Processing
副标题19th International C
编辑Tingwen Huang,Zhigang Zeng,Chi Sing Leung
视频video
概述Fast track conference proceedings.Unique visibility.State of the art research
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Neural Information Processing; 19th International C Tingwen Huang,Zhigang Zeng,Chi Sing Leung Conference proceedings 2012 Springer-Verlag B
描述The five volume set LNCS 7663, LNCS 7664, LNCS 7665, LNCS 7666 and LNCS 7667 constitutes the proceedings of the 19th International Conference on Neural Information Processing, ICONIP 2012, held in Doha, Qatar, in November 2012. .The 423 regular session papers presented were carefully reviewed and selected from numerous submissions. These papers cover all major topics of theoretical research, empirical study and applications of neural information processing research. The 5 volumes represent 5 topical sections containing articles on theoretical analysis, neural modeling, algorithms, applications, as well as simulation and synthesis.
出版日期Conference proceedings 2012
关键词evolutionary algorithms; human-computer interaction; natural language processing; recommender systems; t
版次1
doihttps://doi.org/10.1007/978-3-642-34478-7
isbn_softcover978-3-642-34477-0
isbn_ebook978-3-642-34478-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2012
The information of publication is updating

书目名称Neural Information Processing影响因子(影响力)




书目名称Neural Information Processing影响因子(影响力)学科排名




书目名称Neural Information Processing网络公开度




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0302-9743 containing articles on theoretical analysis, neural modeling, algorithms, applications, as well as simulation and synthesis.978-3-642-34477-0978-3-642-34478-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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Optimization of a Neural Network for Computer Vision Based Fall Detection with Fixed-Point Arithmetihave a major impact on the run-time performance of the neural network. In summary, we achieved a speedup of 48 for multiplication, 39.5 for additions, and 194 for the transfer functions and, thus, realized an embedded real-time fall detection system.
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Estimation of Missing Precipitation Records Using Modular Artificial Neural Networksfrom both networks. The experimental results showed that modular artificial neural networks provided a higher accuracy than single artificial neural network and other conventional methods in terms of mean absolute error.
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Classification of Interview Sheets Using Self-Organizing Maps for Determination of Ophthalmic Examint to be checked is given as the label of the winner neuron for the presented data. It is established that the proposed method achieves as favorable classification accuracy as initial determination made by ophthalmologists.
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PEAQ Compatible Audio Quality Estimation Using Computational Auditory Modelred to the PEAQ advanced version, the proposed estimation system has a considerable improvement in performance both in terms of the correlation and MSE (Mean Square Error). By combining the computational auditory model and PEAQ, our estimation system can be applied to the quality assessment of highly impaired audio.
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A System for Offline Character Recognition Using Auto-encoder Networksease the classification performance further. We observe 94.25% accuracy for the two hidden layer network on Consonant data and 94.1% on Vowel Modifier Dataset which increases to 95.4% for Consonant and 94.8% for Vowel Modifier Dataset after combining classifiers to form an ensemble classifier of 4 different two hidden layer networks.
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