Embedded Files
Peer-reviewed Conference Proceedings
(†: Corresponding Author, #: Equal Contribution)
Peer-reviewed Conference Proceedings
(†: Corresponding Author, #: Equal Contribution)
Park, Soyeon#, Sang Min Yang#, Gyeongho Kim#, Dong Min Kim, Hoon Hee Lee, Jae Gyeong Choi, Sujin Jeon, Sunghoon Lim†, and Hyung Wook Park†. "Accurate monitoring of machining process of Ti-6Al-4V using deep multi-task learning." In 2024 International Conference on Advanced Mechatronic Systems, Institute of Electrical and Electronics Engineers (IEEE), 2024.
Choi, Jae Gyeong, and Sunghoon Lim†. "Multimodal sensor-guided diffusion model for machined surface image synthesis." In 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Ph.D. Consortium, 2024.
Kim, Gyeongho, Sang Min Yang, Sinwon Kim, Dong Min Kim, Sunghoon Lim†, and Hyung Wook Park†. “Tool Wear Prediction in the End Milling Process of Ti-6Al-4V using Bayesian Learning.” In 2022 International Conference on Advanced Mechatronic Systems, Institute of Electrical and Electronics Engineers (IEEE), 2022.
Chatterjee, Sujoy, and Sunghoon Lim†. “A TOPSIS-based Multi-objective Model for Constrained Crowd Judgment Analysis.”, In Eighth AAAI Human Computation and Crowdsourcing (HCOMP-2020), 2020.
Lim, Sunghoon, Conrad S. Tucker†, Kathryn Jablokow, and Bart Pursel. "Quantifying the Mismatch between Course Content and Students’ Dialogue in Online Learning Environments." In ASME 2017 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, American Society of Mechanical Engineers (ASME), 2017. [Design Education (DEC) Technical Committee Best Paper]
Choi, Jae Gyeong, and Sunghoon Lim†. "Multimodal sensor-guided diffusion model for machined surface image synthesis." In 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Ph.D. Consortium, 2024.
Kim, Gyeongho, Sang Min Yang, Sinwon Kim, Dong Min Kim, Sunghoon Lim†, and Hyung Wook Park†. “Tool Wear Prediction in the End Milling Process of Ti-6Al-4V using Bayesian Learning.” In 2022 International Conference on Advanced Mechatronic Systems, Institute of Electrical and Electronics Engineers (IEEE), 2022.
Chatterjee, Sujoy, and Sunghoon Lim†. “A TOPSIS-based Multi-objective Model for Constrained Crowd Judgment Analysis.”, In Eighth AAAI Human Computation and Crowdsourcing (HCOMP-2020), 2020.
Lim, Sunghoon, Conrad S. Tucker†, Kathryn Jablokow, and Bart Pursel. "Quantifying the Mismatch between Course Content and Students’ Dialogue in Online Learning Environments." In ASME 2017 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, American Society of Mechanical Engineers (ASME), 2017. [Design Education (DEC) Technical Committee Best Paper]
International Conference Presentations
(*: Presenter, †: Corresponding Author)
International Conference Presentations
(*: Presenter, †: Corresponding Author)
Kim, Gyeongho*, Sang Min Yang, Sujin Jeon, Soyeon Park, Jae Gyeong Choi, Hyung Wook Park, and Sunghoon Lim†. “Development of a robust tool wear prediction method under novel operating conditions using deep unsupervised domain adaptation and physics-guided adjustment.” INFORMS Annual Meeting, Atlanta, Georgia, 2025.
Park, Soyeon, Sang Min Yang*, Gyeongho Kim, Dong Min Kim, Hoon Hee Lee, Jae Gyeong Choi, Sujin Jeon, Sunghoon Lim†, and Hyung Wook Park†. "Accurate monitoring of machining process of Ti-6Al-4V using deep multi-task learning." 2024 International Conference on Advanced Mechatronic Systems, Shiga, Japan, 2024.
Kim, Gyeongho*, Yun Seok Kang, Sang Min Yang, Jae Gyeong Choi, Gahyun Hwang, Hyung Wook Park, and Sunghoon Lim†. “Continual learning-based remaining useful life prediction of machining tools under varying operating conditions." INFORMS Annual Meeting, Seattle, Washington, 2024.
Choi, Jae Gyeong*, Dong Chan Kim, Miyoung Chung, Hyung Wook Park, and Sunghoon Lim†.“Sensor to Machined Surface Image Generation in CFRP Drilling." IISE Annual Conference & Expo 2023, New Orleans, Louisiana, 2023.
Jeon, Sujin*, Soyeon Park, Hyewon Cho, and Sunghoon Lim†. “Hand gesture recognition without-of-distribution gesture detection using a soft sensor embedded glove." IISE Annual Conference & Expo 2023, New Orleans, Louisiana, 2023.
Kim, Gyeongho*, and Sunghoon Lim†. “Development of a Deep Learning-based Uncertainty-aware Predictive Maintenance Method." IISE Annual Conference & Expo 2023, New Orleans, Louisiana, 2023.
Cho, Hyewon*, Nurbolat Aimakov, Inwoo Park, Myeonghoon Choi, Yerim Kim, Geosong Na, Sunghoon Lim, and Woonggyu Jung†. "Glomerulus quantification with deep learning based on novel multi-modal label-free quantitative phase imaging from a near-infrared (Conference Presentation)." In Quantitative Phase Imaging IX, p. PC123890A. SPIE, 2023.
Kim, Gyeongho*, Sang Min Yang, Sinwon Kim, Dong Min Kim, Sunghoon Lim†, Hyung Wook Park†. “Tool Wear Prediction in the End Milling Process of Ti-6Al-4V using Bayesian Learning.” 2022 International Conference on Advanced Mechatronic Systems, Toyama, Japan, 2022.
Ku, Minjoo*, Gyeongho Kim, and Sunghoon Lim†. “Developing a quality level prediction framework with semi-supervised learning and ordinal classification for UV lamps.” IISE Annual Conference & Expo 2022, Seattle, Washington, 2022.
Hwang, Seong Wook*, and Sunghoon Lim†. “The Charging Infrastructure Design Problem with Electric Taxi Demand Prediction Using Convolutional LSTM.” INFORMS Annual Meeting, Seattle, Washington, 2019.
Park, Soyeon, Sang Min Yang*, Gyeongho Kim, Dong Min Kim, Hoon Hee Lee, Jae Gyeong Choi, Sujin Jeon, Sunghoon Lim†, and Hyung Wook Park†. "Accurate monitoring of machining process of Ti-6Al-4V using deep multi-task learning." 2024 International Conference on Advanced Mechatronic Systems, Shiga, Japan, 2024.
Kim, Gyeongho*, Yun Seok Kang, Sang Min Yang, Jae Gyeong Choi, Gahyun Hwang, Hyung Wook Park, and Sunghoon Lim†. “Continual learning-based remaining useful life prediction of machining tools under varying operating conditions." INFORMS Annual Meeting, Seattle, Washington, 2024.
Choi, Jae Gyeong*, Dong Chan Kim, Miyoung Chung, Hyung Wook Park, and Sunghoon Lim†.“Sensor to Machined Surface Image Generation in CFRP Drilling." IISE Annual Conference & Expo 2023, New Orleans, Louisiana, 2023.
Jeon, Sujin*, Soyeon Park, Hyewon Cho, and Sunghoon Lim†. “Hand gesture recognition without-of-distribution gesture detection using a soft sensor embedded glove." IISE Annual Conference & Expo 2023, New Orleans, Louisiana, 2023.
Kim, Gyeongho*, and Sunghoon Lim†. “Development of a Deep Learning-based Uncertainty-aware Predictive Maintenance Method." IISE Annual Conference & Expo 2023, New Orleans, Louisiana, 2023.
Cho, Hyewon*, Nurbolat Aimakov, Inwoo Park, Myeonghoon Choi, Yerim Kim, Geosong Na, Sunghoon Lim, and Woonggyu Jung†. "Glomerulus quantification with deep learning based on novel multi-modal label-free quantitative phase imaging from a near-infrared (Conference Presentation)." In Quantitative Phase Imaging IX, p. PC123890A. SPIE, 2023.
Kim, Gyeongho*, Sang Min Yang, Sinwon Kim, Dong Min Kim, Sunghoon Lim†, Hyung Wook Park†. “Tool Wear Prediction in the End Milling Process of Ti-6Al-4V using Bayesian Learning.” 2022 International Conference on Advanced Mechatronic Systems, Toyama, Japan, 2022.
Ku, Minjoo*, Gyeongho Kim, and Sunghoon Lim†. “Developing a quality level prediction framework with semi-supervised learning and ordinal classification for UV lamps.” IISE Annual Conference & Expo 2022, Seattle, Washington, 2022.
Hwang, Seong Wook*, and Sunghoon Lim†. “The Charging Infrastructure Design Problem with Electric Taxi Demand Prediction Using Convolutional LSTM.” INFORMS Annual Meeting, Seattle, Washington, 2019.
Domestic Conference Presentations
(*: Presenter, †: Corresponding Author)
Domestic Conference Presentations
(*: Presenter, †: Corresponding Author)
Jeon, Sujin*, and Sunghoon Lim†. “도메인 지식을 반영한 설명 가능한 인공지능 (XAI) 기반의 베어링 잔여 수명 예측." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Park, Soyeon*, and Sunghoon Lim†. “공정 조건의 의미론적 표현 학습을 기반으로 한 강건한 공구 마모 예측 모델 개발." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Lim, Chansung*, Gyeongho Kim, and Sunghoon Lim†. "A deep active learning framework for defect classification of wafer bin maps under noisy labels." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Cheon, Jiyeon*, Dajeong Kam, and Sunghoon Lim†. "Parameter-efficient few-shot class-incremental learning for wearable sensor-based hand gesture recognition." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Kam, Dajeong*, Jiyeon Cheon, and Sunghoon Lim†. "Cross-subject open-set hand gesture recognition using multi-representation fusion CNN with multi-score inference." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Choi, Jihyeok*, Juhyun Kim, Gyeongho Kim, and Sunghoon Lim†. “A cycle-consistent generative model for bidirectional cross-modal translation between industrial tabular and time-series data in an ultraviolet lamp pinch-sealing process." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Han, Geonhee, Juhyun Kim*, and Sunghoon Lim†. “An iTransformer-based approach for BTX yield forecasting in the coke oven gas purification process." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Kim, Gyeongho*, Sujin Jeon, Soyeon Park, and Sunghoon Lim†. “Hybrid data-driven approach for manufacturability prediction of 3D microbial fuel cell anode.” KIIE Fall Conference, Daejeon, Republic of Korea, 2025.
Kim, Gyeongho*, Soyeon Park, Sang Min Yang, Dong Min Kim, Dong Chan Kim, Hoon-Hee Lee, Jae Gyeong Choi, Sujin Jeon, Hyung Wook Park, and Sunghoon Lim†. “Machinability estimation of titanium alloy: An integrated approach with enhanced feature extraction and physics-guided deep multi-task learning.” KORAS Fall Conference, Yeosu, Republic of Korea, 2025.
Kim, Gyeongho*, Sang Min Yang, Jae Gyeong Choi, Sujin Jeon, Soyeon Park, Hyung Wook Park, and Sunghoon Lim†. “새로운 가공 조건에서의 공구 마모 예측을 위한 비지도 도메인 적응 기반 인공지능 방법론 개발.” KSMTE Spring Conference, Gangneung, Republic of Korea, 2025.
Kim, Gyeongho*, Sang Min Yang, Sujin Jeon, Soyeon Park, Jae Gyeong Choi, Hyung Wook Park, and Sunghoon Lim†. “Development of a robust tool wear prediction method under novel operating conditions using deep unsupervised domain adaptation and physics-guided adjustment.” Korean Reliability Society Spring Conference, Jeju, Republic of Korea, 2025.
Kim, Gyeongho*, Sang Min Yang, Jae Gyeong Choi, Sujin Jeon, Soyeon Park, Hyung Wook Park, and Sunghoon Lim†. “Development of a physics-guided deep domain adaptive regression method for robust tool wear prediction under novel operating conditions.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2025.
Jeon, Sujin*, Yun Seok Kang, Hyung Wook Park, and Sunghoon Lim†. “설명 가능한 인공지능(XAI)을 활용한 로봇팔 트리밍 공정의 공구 마모 예측.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2025.
Park, Soyeon*, Gyeongho Kim, Sang Min Yang, Hyung Wook Park, and Sunghoon Lim†. “Predicting Machinability Using Cross-task Attention-based Multi-task Learning.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2025.
Kim, Gyeongho*, Yun Seok Kang, Sang Min Yang, Jae Gyeong Choi, Gahyun Hwang, Juhyun Kim, Chansung Lim, Hyung Wook Park, and Sunghoon Lim†. “Continual learning-based remaining useful life prediction of machining tools under varying operating conditions.” Korean Reliability Society Fall Conference, Gyeongju, Republic of Korea, 2024.
Kim, Gyeongho*, Jae Gyeong Choi, Sujin Jeon, Soyeon Park, Juhyun Kim, Ji Yeon Cheon, Chansung Lim, and Sunghoon Lim†. “Hybrid Deep Active Learning Under Low-Budget Scenarios for Efficient Fault Detection.” KIIE Fall Conference, Seoul, Republic of Korea, 2024.
Park, Soyeon*, Sang Min Yang, Gyeongho Kim, Ji Yeon Cheon, and Sunghoon Lim†. “Uncertainty-aware machining process monitoring using multi-task learning.” KIIE Fall Conference, Seoul, Republic of Korea, 2024.
Kim, Gyeongho*, Yunseok Kang, Sang Min Yang, Jae Gyeong Choi, Gahyun Hwang, Juhyun Kim, Ji Yeon Cheon, Chansung Lim, Hyung Wook Park, and Sunghoon Lim†.“Fisher-informed continual learning for remaining useful life prediction of machining tools under varying operating conditions.” KSMTE Annual Spring Conference 2024, Gangneung, Republic of Korea, 2024.
Park, Soyeon*, and Sunghoon Lim†. “Lightweight anomalous object detection in a fixed-camera environment.” KIIE Fall Conference, Ulsan, Republic of Korea, 2023.
Kim, Gyeongho*, Sang Min Yang, Sin Won Kim, Do Young Kim, Jae Gyeong Choi, Hyung Wook Park, and Sunghoon Lim†. "Deep Learning-based Tool Wear Prediction under Multiple Machining Conditions." PHM Korea 2023, Seoul, Republic of Korea, 2023.
Kim, Gyeongho*, Soyeon Park, Jae Gyeong Choi, Hyeokjoon Choi, and Sunghoon Lim†.“Grinding Process Parameter Optimization Using Machine Learning Techniques.” Korea Data Mining Society Summer Conference, Gangneung, Republic of Korea, 2023.
Kim, Gyeongho*, Sangmin Yang, and Sunghoon Lim†. “Development of a Bayesian-based Uncertainty-aware Tool Wear Prediction Model in the End Milling Process.” KIIE Fall Conference, Incheon, Republic of Korea, 2022.
Ku, Minjoo*, and Sunghoon Lim†. “Development of a deep learning-based anomaly detection model using multivariate time series manufacturing data.” KIIE Fall Conference, Incheon, Republic of Korea, 2022.
Jeon, Sujin*, Soyeon Park, Hyewon Cho, and Sunghoon Lim†. “Multistep classification of static and dynamic finger gestures using a soft sensor embedded glove.” KIIE Fall Conference, Incheon, Republic of Korea, 2022.
Kim, Gyeongho*, and Sunghoon Lim†. “Development of a Remaining Useful Life Estimation Method Using Transformer and a Reweighting Technique.” Korea Data Mining Society Summer Conference, Busan, Republic of Korea, 2022.
Cho, Hyewon*, Sujin Jeon, Soyeon Park, and Sunghoon Lim†. “Development of a deep learning-based real-time gesture detection and classification model using a wearable sensing glove.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2022.
Choi, Jae Gyeong*, Dong Chan Kim, Miyoung Chung, Sunghoon Lim†, and Hyung Wook Park†. “A multimodal 1D convolutional neural network for delamination prediction in carbon fiber reinforced plastic (CFRP) drilling processes.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2022.
Choi, Jae Gyeong*, Chan Woo Kong, Gyeongho Kim, and Sunghoon Lim†. “Car crash detection using ensemble deep learning and multimodal data from dashboard cameras.” Korea Safety Management & Science Fall Conference, Ulsan, Republic of Korea, 2021.
Kim, Gyeongho, Jae Gyeong Choi, Minjoo Ku, Hyewon Cho, and Sunghoon Lim*,†. “Developing a deep learning-based fault detection model for plastic injection molding for car parts companies.” KSQM Spring Conference, Seoul, Republic of Korea, 2021.
Kim, Sun Jun*, and Sunghoon Lim†. “A deep learning-based hybrid recommender system with fake review filtering for e-commerce customers.” KIIE Fall Conference, Seoul, Republic of Korea, 2020.
Choi, Jae Gyeong*, Chan Woo Kong, and Sunghoon Lim†. “Developing machine-learning-based car crash detection systems using video and audio data.” KIIE Fall Conference, Seoul, Republic of Korea, 2019.
Baek, DaeSeon, and Sunghoon Lim*,†. “Smart farming: Developing growth programs and reforming environmental conditions for hog raising using machine vision and deep learning.” KIIE/KORMS/KSS Joint Spring Conference, Gwangju, Republic of Korea, 2019.
Park, Soyeon*, and Sunghoon Lim†. “공정 조건의 의미론적 표현 학습을 기반으로 한 강건한 공구 마모 예측 모델 개발." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Lim, Chansung*, Gyeongho Kim, and Sunghoon Lim†. "A deep active learning framework for defect classification of wafer bin maps under noisy labels." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Cheon, Jiyeon*, Dajeong Kam, and Sunghoon Lim†. "Parameter-efficient few-shot class-incremental learning for wearable sensor-based hand gesture recognition." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Kam, Dajeong*, Jiyeon Cheon, and Sunghoon Lim†. "Cross-subject open-set hand gesture recognition using multi-representation fusion CNN with multi-score inference." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Choi, Jihyeok*, Juhyun Kim, Gyeongho Kim, and Sunghoon Lim†. “A cycle-consistent generative model for bidirectional cross-modal translation between industrial tabular and time-series data in an ultraviolet lamp pinch-sealing process." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Han, Geonhee, Juhyun Kim*, and Sunghoon Lim†. “An iTransformer-based approach for BTX yield forecasting in the coke oven gas purification process." KIIE/KORMS Joint Spring Conference, Gyeongju, Republic of Korea, 2026.
Kim, Gyeongho*, Sujin Jeon, Soyeon Park, and Sunghoon Lim†. “Hybrid data-driven approach for manufacturability prediction of 3D microbial fuel cell anode.” KIIE Fall Conference, Daejeon, Republic of Korea, 2025.
Kim, Gyeongho*, Soyeon Park, Sang Min Yang, Dong Min Kim, Dong Chan Kim, Hoon-Hee Lee, Jae Gyeong Choi, Sujin Jeon, Hyung Wook Park, and Sunghoon Lim†. “Machinability estimation of titanium alloy: An integrated approach with enhanced feature extraction and physics-guided deep multi-task learning.” KORAS Fall Conference, Yeosu, Republic of Korea, 2025.
Kim, Gyeongho*, Sang Min Yang, Jae Gyeong Choi, Sujin Jeon, Soyeon Park, Hyung Wook Park, and Sunghoon Lim†. “새로운 가공 조건에서의 공구 마모 예측을 위한 비지도 도메인 적응 기반 인공지능 방법론 개발.” KSMTE Spring Conference, Gangneung, Republic of Korea, 2025.
Kim, Gyeongho*, Sang Min Yang, Sujin Jeon, Soyeon Park, Jae Gyeong Choi, Hyung Wook Park, and Sunghoon Lim†. “Development of a robust tool wear prediction method under novel operating conditions using deep unsupervised domain adaptation and physics-guided adjustment.” Korean Reliability Society Spring Conference, Jeju, Republic of Korea, 2025.
Kim, Gyeongho*, Sang Min Yang, Jae Gyeong Choi, Sujin Jeon, Soyeon Park, Hyung Wook Park, and Sunghoon Lim†. “Development of a physics-guided deep domain adaptive regression method for robust tool wear prediction under novel operating conditions.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2025.
Jeon, Sujin*, Yun Seok Kang, Hyung Wook Park, and Sunghoon Lim†. “설명 가능한 인공지능(XAI)을 활용한 로봇팔 트리밍 공정의 공구 마모 예측.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2025.
Park, Soyeon*, Gyeongho Kim, Sang Min Yang, Hyung Wook Park, and Sunghoon Lim†. “Predicting Machinability Using Cross-task Attention-based Multi-task Learning.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2025.
Kim, Gyeongho*, Yun Seok Kang, Sang Min Yang, Jae Gyeong Choi, Gahyun Hwang, Juhyun Kim, Chansung Lim, Hyung Wook Park, and Sunghoon Lim†. “Continual learning-based remaining useful life prediction of machining tools under varying operating conditions.” Korean Reliability Society Fall Conference, Gyeongju, Republic of Korea, 2024.
Kim, Gyeongho*, Jae Gyeong Choi, Sujin Jeon, Soyeon Park, Juhyun Kim, Ji Yeon Cheon, Chansung Lim, and Sunghoon Lim†. “Hybrid Deep Active Learning Under Low-Budget Scenarios for Efficient Fault Detection.” KIIE Fall Conference, Seoul, Republic of Korea, 2024.
Park, Soyeon*, Sang Min Yang, Gyeongho Kim, Ji Yeon Cheon, and Sunghoon Lim†. “Uncertainty-aware machining process monitoring using multi-task learning.” KIIE Fall Conference, Seoul, Republic of Korea, 2024.
Kim, Gyeongho*, Yunseok Kang, Sang Min Yang, Jae Gyeong Choi, Gahyun Hwang, Juhyun Kim, Ji Yeon Cheon, Chansung Lim, Hyung Wook Park, and Sunghoon Lim†.“Fisher-informed continual learning for remaining useful life prediction of machining tools under varying operating conditions.” KSMTE Annual Spring Conference 2024, Gangneung, Republic of Korea, 2024.
Park, Soyeon*, and Sunghoon Lim†. “Lightweight anomalous object detection in a fixed-camera environment.” KIIE Fall Conference, Ulsan, Republic of Korea, 2023.
Kim, Gyeongho*, Sang Min Yang, Sin Won Kim, Do Young Kim, Jae Gyeong Choi, Hyung Wook Park, and Sunghoon Lim†. "Deep Learning-based Tool Wear Prediction under Multiple Machining Conditions." PHM Korea 2023, Seoul, Republic of Korea, 2023.
Kim, Gyeongho*, Soyeon Park, Jae Gyeong Choi, Hyeokjoon Choi, and Sunghoon Lim†.“Grinding Process Parameter Optimization Using Machine Learning Techniques.” Korea Data Mining Society Summer Conference, Gangneung, Republic of Korea, 2023.
Kim, Gyeongho*, Sangmin Yang, and Sunghoon Lim†. “Development of a Bayesian-based Uncertainty-aware Tool Wear Prediction Model in the End Milling Process.” KIIE Fall Conference, Incheon, Republic of Korea, 2022.
Ku, Minjoo*, and Sunghoon Lim†. “Development of a deep learning-based anomaly detection model using multivariate time series manufacturing data.” KIIE Fall Conference, Incheon, Republic of Korea, 2022.
Jeon, Sujin*, Soyeon Park, Hyewon Cho, and Sunghoon Lim†. “Multistep classification of static and dynamic finger gestures using a soft sensor embedded glove.” KIIE Fall Conference, Incheon, Republic of Korea, 2022.
Kim, Gyeongho*, and Sunghoon Lim†. “Development of a Remaining Useful Life Estimation Method Using Transformer and a Reweighting Technique.” Korea Data Mining Society Summer Conference, Busan, Republic of Korea, 2022.
Cho, Hyewon*, Sujin Jeon, Soyeon Park, and Sunghoon Lim†. “Development of a deep learning-based real-time gesture detection and classification model using a wearable sensing glove.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2022.
Choi, Jae Gyeong*, Dong Chan Kim, Miyoung Chung, Sunghoon Lim†, and Hyung Wook Park†. “A multimodal 1D convolutional neural network for delamination prediction in carbon fiber reinforced plastic (CFRP) drilling processes.” KIIE/KORMS Joint Spring Conference, Jeju, Republic of Korea, 2022.
Choi, Jae Gyeong*, Chan Woo Kong, Gyeongho Kim, and Sunghoon Lim†. “Car crash detection using ensemble deep learning and multimodal data from dashboard cameras.” Korea Safety Management & Science Fall Conference, Ulsan, Republic of Korea, 2021.
Kim, Gyeongho, Jae Gyeong Choi, Minjoo Ku, Hyewon Cho, and Sunghoon Lim*,†. “Developing a deep learning-based fault detection model for plastic injection molding for car parts companies.” KSQM Spring Conference, Seoul, Republic of Korea, 2021.
Kim, Sun Jun*, and Sunghoon Lim†. “A deep learning-based hybrid recommender system with fake review filtering for e-commerce customers.” KIIE Fall Conference, Seoul, Republic of Korea, 2020.
Choi, Jae Gyeong*, Chan Woo Kong, and Sunghoon Lim†. “Developing machine-learning-based car crash detection systems using video and audio data.” KIIE Fall Conference, Seoul, Republic of Korea, 2019.
Baek, DaeSeon, and Sunghoon Lim*,†. “Smart farming: Developing growth programs and reforming environmental conditions for hog raising using machine vision and deep learning.” KIIE/KORMS/KSS Joint Spring Conference, Gwangju, Republic of Korea, 2019.
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