Jongmin Park
Seoul National University
12 Papers
19 Citations
Jongmin Park is an academic researcher from Seoul National University. The author has contributed to research in topics: Computer science & Fault (power engineering). The author has an hindex of 3, co-authored 4 publications.
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Papers
A Semi-Supervised Autoencoder With an Auxiliary Task (SAAT) for Power Transformer Fault Diagnosis Using Dissolved Gas Analysis
Sunuwe Kim,Soo-Ho Jo,Wongon Kim,Jongmin Park,Jingyo Jeong,Yeongmin Han,Daeil Kim,Byeng D. Youn +7 more
TL;DR: Comparisons confirm that the proposed SAAT-based health feature space approach outperforms SSAE without the auxiliary task, existing methods, and state-of-the-art deep learning algorithms, in terms of defining health degradation performance.
Learning from even a weak teacher: Bridging rule-based Duval method and a deep neural network for power transformer fault diagnosis
TL;DR: Li et al. as discussed by the authors proposed a new framework, named BDD, which bridges Duval's method with a deep neural network (DNN) approach for power transformer fault diagnosis using dissolved gas analysis (DGA).
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Tissue-engineered heart valve leaflets: an effective method for seeding autologous cells on scaffolds.
Wongon Kim,Jongmin Park,Y. N. Park,Chang Mo Hwang,Y. H. Jo,Byeong-Gu Min,Chul Jong Yoon,T. Y. Lee +7 more
TL;DR: Seding autologous cells with a medium containing collagen onto the scaffold showed the largest cell population and might generate the best matrix on the scaffolds.
13
Multi-head de-noising autoencoder-based multi-task model for fault diagnosis of rolling element bearings under various speed conditions
Jongmin Park,Jinoh Yoo,Taehyung Kim,Jong Moon Ha,Byeng D. Youn +4 more
TL;DR: A multi-head de-noising autoencoder and multi-task learning strategy to robustly extract features under various speed conditions, while effectively disentangling the speed- and fault-related information is proposed.
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