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Titlebook: Brain Informatics; International Confer Fabio Massimo Zanzotto,Shusaku Tsumoto,Yiyu Yao Conference proceedings 2012 Springer-Verlag Berlin

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樓主: JOLT
21#
發(fā)表于 2025-3-25 05:32:20 | 只看該作者
Ground Water Recovery and Treatmentsible to record brain activity in real-time and discover patterns to relate it to emotional states. This paper describes a machine learning approach to detect emotion from brain activity, recorded as electroencephalograph (EEG) with the Emotic Epoc device, during auditory stimulation. First, we extr
22#
發(fā)表于 2025-3-25 08:40:45 | 只看該作者
https://doi.org/10.1007/978-3-030-80076-5uring methods in graph theory: phase locking value (PLV) and visibility graph similarity (VGS). It develops a new linear horizontal visibility graph constructing algorithm, analyzes its constructing complexity, and tests its feature performance via the sleep stages identification application. Six fe
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發(fā)表于 2025-3-25 15:13:44 | 只看該作者
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發(fā)表于 2025-3-25 16:35:54 | 只看該作者
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發(fā)表于 2025-3-25 22:31:27 | 只看該作者
978-3-642-35138-9Springer-Verlag Berlin Heidelberg 2012
26#
發(fā)表于 2025-3-26 00:25:37 | 只看該作者
27#
發(fā)表于 2025-3-26 04:36:34 | 只看該作者
BatGaze: A New Tool to Measure Depth Features at the Center of Gaze during Free Viewingf gaze during free viewing are simply not know. We combined mobile eye tracking and depth imaging in order to record such missing stimulus material. Here we report on this newly developed system, called BatGaze, and on a first experimental validation of it. We believe that it will become a very valu
28#
發(fā)表于 2025-3-26 09:34:58 | 只看該作者
A Brain Informatics Approach to Explain the Oblique Effect via Depth Statisticsnvey more information about relevant depth features than other oriented filters. More specifically, we find that vertical filter responses are much more informative about gap and orientation discontinuities in the depth images than other filters. We show that this is an inherent property of the inve
29#
發(fā)表于 2025-3-26 16:40:48 | 只看該作者
Information-Theoretic Based Feature Selection for Multi-Voxel Pattern Analysis of fMRI Data a publicly available fMRI data set that has been widely used to benchmark MVPA performance [1]. The computational results suggest that feature selection based on the MI ranking can drastically improve the classification accuracy. Additionally, high-ranked features provide meaningful insights into t
30#
發(fā)表于 2025-3-26 19:20:36 | 只看該作者
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