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dc.contributor.authorWang, Kai-Yenen_US
dc.contributor.authorHo, Yun-Lungen_US
dc.contributor.authorHuang, Yu-Deen_US
dc.contributor.authorFang, Wai-Chien_US
dc.date.accessioned2019-12-13T01:12:51Z-
dc.date.available2019-12-13T01:12:51Z-
dc.date.issued2019-01-01en_US
dc.identifier.isbn978-1-5386-7884-8en_US
dc.identifier.urihttp://hdl.handle.net/11536/153280-
dc.description.abstractEmotions play a significant role in the field of affective computing and Human-Computer Interfaces(HCI). In this paper, we propose an intelligent human emotion detection system based on EEG features with a multi-channel fused processing. We also proposed an advanced convolutional neural network that was implemented in VLSI hardware design. This hardware design can accelerate both the training and classification processes and meet real-time system requirements for fast emotion detection. The performance of this design was validated using DEAP [1] database with datasets from 32 subjects, the mean classification accuracy achieved is 83.88%.en_US
dc.language.isoen_USen_US
dc.subjectEmotion Recognitionen_US
dc.subjectConvolutional Neural Networken_US
dc.subjectDeep Learningen_US
dc.subjectHardware Machine Learningen_US
dc.subjectReal-time EEG Systemen_US
dc.subjectAffective Computingen_US
dc.titleDesign of Intelligent EEG System for Human Emotion Recognition with Convolutional Neural Networken_US
dc.typeProceedings Paperen_US
dc.identifier.journal2019 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS 2019)en_US
dc.citation.spage142en_US
dc.citation.epage145en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000493095400031en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper