Search Results - "Choi, Hongjun"

Data-driven fault diagnosis based on coal-fired power plant operating data by Choi, Hongjun, Kim, Chang-Wan, Kwon, Daeil

“…This paper discusses data-driven fault diagnosis of the power plant reheater tube leakage based on their operating data. From the temperature sensors, fault…”
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Exploring the Influence of YouTube on Digital Health Literacy and Health Exercise Intentions: The Role of Parasocial Relationships by Kim, Jongho, Youm, Heeok, Kim, Sujin, Choi, Hongjun, Kim, Dohee, Shin, Sungeun, Chung, Jinwook

“…The purpose of this study was to analyze the mediating role of digital health literacy and the moderating effect of parasocial relationships on the…”
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Analysis of Cooling Characteristics of Permanent Magnet Synchronous Motor with Different Water Jacket Design Using Electromagnetic–Thermal Fluid Coupled Analysis and Design of Experiment by Jeon, Kyunghun, Park, Myungwoo, Park, Jongjin, Choi, Hongjun, Lee, Ki-Deok, Lee, Jeong-Jong, Kim, Chang-Wan

“…Electrical losses are converted into thermal energy in motors, which heats each component. It is a significant factor in decreasing motor mechanical…”
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Leveraging angular distributions for improved knowledge distillation by Jeon, Eun Som, Choi, Hongjun, Shukla, Ankita, Turaga, Pavan

“…Knowledge distillation as a broad class of methods has led to the development of lightweight and memory efficient models, using a pre-trained model with a…”
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Building Reliable and Robust Deep Neural Networks With Improved Representations Using Model Distillation and Deep Constraints by Choi, Hongjun

“…This thesis encompasses a comprehensive research effort dedicated to overcoming the critical bottlenecks that hinder the current generation of neural networks,…”
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An extended Kalman filter for mouse tracking by Choi, Hongjun, Kim, Mingi, Lee, Onseok

“…Animal tracking is an important tool for observing behavior, which is useful in various research areas. Animal specimens can be tracked using dynamic models…”
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Towards Secure and Reliable Robotic Vehicles with Holistic Modeling and Program Analysis by Choi, Hongjun

“…Cyber-Physical Systems (CPS) are integrated systems that consist of the computational and physical components with network communication to support operation…”
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Topological persistence guided knowledge distillation for wearable sensor data by Jeon, Eun Som, Choi, Hongjun, Shukla, Ankita, Wang, Yuan, Lee, Hyunglae, Buman, Matthew P., Turaga, Pavan

“…Deep learning methods have achieved a lot of success in various applications involving converting wearable sensor data to actionable health insights. A common…”
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Constrained Adaptive Distillation Based on Topological Persistence for Wearable Sensor Data by Jeon, Eun Som, Choi, Hongjun, Shukla, Ankita, Wang, Yuan, Buman, Matthew P., Turaga, Pavan

“…Wearable sensor data analysis with persistence features generated by topological data analysis (TDA) has achieved great success in various applications, and…”
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Topological Knowledge Distillation for Wearable Sensor Data by Jeon, Eun Som, Choi, Hongjun, Shukla, Ankita, Wang, Yuan, Buman, Matthew P., Turaga, Pavan

“…Converting wearable sensor data to actionable health insights has witnessed large interest in recent years. Deep learning methods have been utilized in and…”
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Understanding the Role of Mixup in Knowledge Distillation: An Empirical Study by Choi, Hongjun, Jeon, Eun Som, Shukla, Ankita, Turaga, Pavan

“…Mixup is a popular data augmentation technique based on creating new samples by linear interpolation between two given data samples, to improve both the…”
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FRI-458-Response evaluation using modified RECIST criteria predict outcomes better than RECIST 1.1 criteria in patients with HCC treated with Yttrium-90 radioembolization by Choi, HongJun, Lim, Tae Seop, Jeon, Mi Young, Cho, In Rae, Kim, Beom Kyung, Park, Jun Yong, Kim, Do Young, Ahn, Sang Hoon, Han, Kwang-Hyub, Kim, Seung Up, Lee, Jae Seung

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White-Box Program Tuning by Lee, Wen-Chuan, Liu, Yingqi, Liu, Peng, Ma, Shiqing, Choi, Hongjun, Zhang, Xiangyu, Gupta, Rajiv

“…Many programs or algorithms are largely parameterized, especially those based on heuristics. The quality of the results depends on the parameter setting…”
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AMC-Loss: Angular Margin Contrastive Loss for Improved Explainability in Image Classification by Choi, Hongjun, Som, Anirudh, Turaga, Pavan

“…Deep-learning architectures for classification problems involve the cross-entropy loss sometimes assisted with auxiliary loss functions like center loss,…”
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Early wakeup: improving the drowsy cache performance by SHIM, Sunghoon, CHUNG, Sungwoo, CHOI, Hongjun, KIM, Cheol Hong

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PI-Net: A Deep Learning Approach to Extract Topological Persistence Images by Som, Anirudh, Choi, Hongjun, Ramamurthy, Karthikeyan Natesan, Buman, Matthew P., Turaga, Pavan

“…Topological features such as persistence diagrams and their functional approximations like persistence images (PIs) have been showing substantial promise for…”
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Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization by Choi, Hongjun, Thiagarajan, Jayaraman J, Glatt, Ruben, Liu, Shusen

“…In this work, we investigate the fundamental trade-off regarding accuracy and parameter efficiency in the parameterization of neural network weights using…”
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ROCAS: Root Cause Analysis of Autonomous Driving Accidents via Cyber-Physical Co-mutation by Feng, Shiwei, Ye, Yapeng, Shi, Qingkai, Cheng, Zhiyuan, Xu, Xiangzhe, Cheng, Siyuan, Choi, Hongjun, Zhang, Xiangyu

“…As Autonomous driving systems (ADS) have transformed our daily life, safety of ADS is of growing significance. While various testing approaches have emerged to…”
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Understanding the Role of Mixup in Knowledge Distillation: An Empirical Study by Choi, Hongjun, Jeon, Eun Som, Shukla, Ankita, Turaga, Pavan

“…Mixup is a popular data augmentation technique based on creating new samples by linear interpolation between two given data samples, to improve both the…”
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Unmasking Correlations in Nuclear Cross Sections with Graph Neural Networks by Mitra, Sinjini, Choi, Hongjun, Liu, Shusen, Glatt, Ruben, Wendt, Kyle, Schunck, Nicolas

“…In this work, we explore the use of deep learning techniques to learn the relationships between nuclear cross-sections across the chart of isotopes. As a proof…”
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