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Titlebook: Brain Informatics; 13th International C Mufti Mahmud,Stefano Vassanelli,Ning Zhong Conference proceedings 2020 Springer Nature Switzerland

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發(fā)表于 2025-3-21 18:37:14 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Brain Informatics
期刊簡(jiǎn)稱(chēng)13th International C
影響因子2023Mufti Mahmud,Stefano Vassanelli,Ning Zhong
視頻videohttp://file.papertrans.cn/191/190197/190197.mp4
學(xué)科分類(lèi)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Brain Informatics; 13th International C Mufti Mahmud,Stefano Vassanelli,Ning Zhong Conference proceedings 2020 Springer Nature Switzerland
影響因子.This book constitutes the refereed proceedings of the 13th International Conference on Brain Informatics, BI 2020, held in Padua, Italy, in September 2020. The conference was held virtually due to the COVID-19 pandemic...The 33 full papers were carefully reviewed and selected from 57 submissions. The papers are organized in the following topical sections: cognitive and computational foundations of brain science; investigations of human information processing systems; brain big data analytics, curation and management; informatics paradigms for brain and mental health research; and brain-machine intelligence and brain-inspired computing..
Pindex Conference proceedings 2020
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書(shū)目名稱(chēng)Brain Informatics影響因子(影響力)




書(shū)目名稱(chēng)Brain Informatics影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Brain Informatics網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Brain Informatics網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Brain Informatics被引頻次




書(shū)目名稱(chēng)Brain Informatics被引頻次學(xué)科排名




書(shū)目名稱(chēng)Brain Informatics年度引用




書(shū)目名稱(chēng)Brain Informatics年度引用學(xué)科排名




書(shū)目名稱(chēng)Brain Informatics讀者反饋




書(shū)目名稱(chēng)Brain Informatics讀者反饋學(xué)科排名




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The Effect of Loss-Aversion on Strategic Behaviour of Players in Divergent Interest Tacit Coordinatiion problems. The overarching aim of our study was to model the effect of loss aversion on individual player behavior in divergent interest tacit coordination games. Based on a large-scale behavioral data we have designed a model predicting the total number of points players allocate to themselves a
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Temporal-Spatial-Spectral Investigation of Brain Network Dynamics in Human Speech Perceptionly and accurately. Current investigation using neuroimaging and electrophysiological techniques laid the foundation of our understanding regarding the brain activities in the spatial, temporal, and spectral domains. However, a comprehensive view integrating these three aspects yet to be achieved by
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Precise Estimation of Resting State Functional Connectivity Using Empirical Mode Decompositioneasure of neuronal activity or the existing deconvolution approaches assume that hemodynamic response function (HRF), which modulates the neuronal activities, is uniform across the brain regions or across the time course. We propose a novel approach using empirical mode decomposition (EMD), to reduc
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