Congratulations!!! Eunsong’s work on “A Learnable Counter-condition Analysis Framework for Functional Connectivity-based Neurological Disorder Diagnosis,” has been accepted for publication in IEEE-TMI.
Category: <span>Lab News</span>
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Accepted to IEEE-TMI
Congratulations!!! Wonsik’s work on “EAG-RS: A Novel Explainability-guided ROI Selection Framework for ASD Diagnosis via Inter-regional Relation Learning,” has been accepted for publication in IEEE-TMI.
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3 Papers Accepted to JKAIA 2023
Congratulations. 3 papers by Eunsong, Eunjin, and Kwanseok are accepted for presentation at JKAIA2023.
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석흥일 교수님, 식약처장 표창 수상
2023년 혁신의료기기 산업 발전에 대한 우수 공적자로 선정되어 식품의약품안전처장 표창을 수상하였다. Professor Heung-Il Suk received the “Award for Contribution to the Development of the Innovative Medical Device Industry” from the Ministry of Food and Drug Safety.
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Accepted to Scientific Reports
Congratulations!!! Junghyo’s work on “Module of Axis-based Nexus Attention for Weakly Supervised Object Localization” has been accepted for publication at Scientific Reports.
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Accepted to IEEE-TPAMI
Congratulations!!! Seungwoo’s work on “Deep Efficient Continuous Manifold Learning for Time Series Modeling,” has been accepted for publication in IEEE-TPAMI.
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Accepted to Journal of Cleaner Production
Congratulations!!! Do-Yeon’s work on “Spatiotemporal Graph Neural Networks for Predicting Mid-to-Long-Term PM2.5 Concentrations” has been accepted for publication in the Journal of Cleaner Production (JCR-IF: 11.1).
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고원준 박사, 성신여대 조교수 임용
우리 연구실의 박사졸업생, 고원준 박사가 성신여자대학교 조교수로 임용되었습니다. 그의 학문적 성취와 헌신에 박수를 보냅니다. 향후의 성공과 발전을 기대합니다. 🌟
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Accepted to IEEE-TNNLS
Congratulations!!! Jaein’s work on “Site-Invariant Meta-Modulation Learning for Multi-Site Autism Spectrum Disorders Diagnosis” has been accepted for publication in IEEE-TNNLS.
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Accepted to IEEE-TNNLS
Congratulations!!! Eunji’s paper “Medical Transformer: Universal Encoder for 3D Brain MRI Analysis” has been accepted for publication in IEEE Transactions on Neural Networks and Learning Systems. E. Jun, S. Jeong, D.-W. Heo, and H.-I. Suk, “Medical Transformer: Universal Brain Encoder for 3D MRI Analysis,” IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Accepted, 2023....