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Titlebook: Brain-Inspired Computing; Second International Katrin Amunts,Lucio Grandinetti,Nicolai Petkov Conference proceedings 2016 Springer Internat

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发表于 2025-3-21 16:10:50 | 显示全部楼层 |阅读模式
期刊全称Brain-Inspired Computing
期刊简称Second International
影响因子2023Katrin Amunts,Lucio Grandinetti,Nicolai Petkov
视频video
发行地址Includes supplementary material:
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Brain-Inspired Computing; Second International Katrin Amunts,Lucio Grandinetti,Nicolai Petkov Conference proceedings 2016 Springer Internat
影响因子.This book constitutes revised selected papers from the Second International Workshop on Brain-Inspired Computing, BrainComp 2015, held in Cetraro, Italy, in July 2015. . The 14 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with brain structure and function; computational models and brain-inspired computing methods with practical applications; high performance computing; and visualization for brain simulations. .
Pindex Conference proceedings 2016
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https://doi.org/10.1007/978-3-642-39724-0 requirements specified. Therefore, a novel asymmetrical multiprocessor architecture for embedded control systems is presented. Resembling the structure of the human brain, it inherently supports temporal determinism.
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Classification of FDG-PET Brain Data by Generalized Matrix Relevance LVQ,mponent Analysis in the Scaled Subprofile Model approach. The performance of the GMLVQ classifiers is evaluated in a Leave-One-Out framework. Comparison with earlier results shows that GMLVQ and Support Vector Machine with linear kernel achieve comparable performance while both outperform a C4-5 Decision Tree classifier.
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Sentiment Analysis and Affective Computing: Methods and Applications,e discussion of the main processing techniques and applications. The paper concludes with a discussion relative to a new approach based on the integration of sentiment analysis and affective computing to obtain a more accurate and reliable detection of emotions and feelings for applications in the life sciences.
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Mergers and Acquisitions Year Bookble data set, namely the MIVIA road events data set. The results that we achieve (recognition rate equal to . and false positive rate lower than .) and the comparison with existing methods demonstrate the effectiveness of the proposed bio-inspired filters for audio analysis.
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