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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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發(fā)表于 2025-3-21 16:10:50 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Brain-Inspired Computing
期刊簡稱Second International
影響因子2023Katrin Amunts,Lucio Grandinetti,Nicolai Petkov
視頻videohttp://file.papertrans.cn/191/190303/190303.mp4
發(fā)行地址Includes supplementary material:
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Brain-Inspired Computing; Second International Katrin Amunts,Lucio Grandinetti,Nicolai Petkov Conference proceedings 2016 Springer Internat
影響因子.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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書目名稱Brain-Inspired Computing影響因子(影響力)




書目名稱Brain-Inspired Computing影響因子(影響力)學(xué)科排名




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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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發(fā)表于 2025-3-22 09:46:46 | 只看該作者
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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