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Lim, Sunghoon (임성훈)

Department
Department of Industrial Engineering(산업공학과)
Website
http://sunghoonlim.unist.ac.kr
Lab
Industrial Intelligence Lab. (산업지능 연구실)
Research Keywords
기계학습, 인공지능, 산업인공지능, Artificial Intelligence (AI), Machine Learning, Industrial Artificial Intelligence
Research Interests
Research at Industrial Intelligence Laboratory"Development of machine learning models for effective knowledge discovery from the real industry" TopicsMachine Learning / Deep Learning(Unstructured) Data MiningIndustrial Artificial Intelligence (AI+X)Computer VisionSocial Network Analysis / CrowdsourcingApplicationsManufacturing (e.g., Smart Factory, Predictive Maintenance, Anomaly Detection, Additive Manufacturing)Safety Management (e.g., Car Crash Detection)Customer Feedback Analysis Using Online Data (e.g., Social Media, Online Customer Reviews, Recommender Systems)Healthcare (e.g., Disease Discovery)etc.
This table browses all dspace content
Issue DateTitleAuthor(s)TypeViewAltmetrics
2022-06A Deep Learning-based Cryptocurrency Price Prediction Model That Uses On-chain DataKim, Gyeongho; Shin, Dong-Hyun; Choi, Jae Gyeong, et alARTICLE228 A Deep Learning-based Cryptocurrency Price Prediction Model That Uses On-chain Data
2022-04The Charging Infrastructure Design Problem with Electric Taxi Demand Prediction Using Convolutional LSTMHwang, Seong Wook; Lim, SunghoonARTICLE159 The Charging Infrastructure Design Problem with Electric Taxi Demand Prediction Using Convolutional LSTM
2022-04An EfficientNet-Based Weighted Ensemble Model for Industrial Machine Malfunction Detection Using Acoustic SignalsTama, Bayu Adhi; Vania, Malinda; Kim, Iljung, et alARTICLE148 An EfficientNet-Based Weighted Ensemble Model for Industrial Machine Malfunction Detection Using Acoustic Signals
2022-04Development of an Interpretable Maritime Accident Prediction System Using Machine Learning TechniquesKim, Gyeongho; Lim, SunghoonARTICLE127 Development of an Interpretable Maritime Accident Prediction System Using Machine Learning Techniques
2022-03A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban PlanningChatterjee, Sujoy; Lim, SunghoonARTICLE149 A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning
2022-02Characterization of power demand and energy consumption for fused filament fabrication using CFR-PEEKKim, Kyudong; Noh, Heena; Park, Kijung, et alARTICLE138 Characterization of power demand and energy consumption for fused filament fabrication using CFR-PEEK
2021-12A deep learning-based time series model with missing value handling techniques to predict various types of liquid cargo trafficLim, Sunghoon; Kim, Sun Jun; Park, YoungJae, et alARTICLE490 A deep learning-based time series model with missing value handling techniques to predict various types of liquid cargo traffic
2021-12DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market predictionTuarob, Suppawong; Wettayakorn, Poom; Phetchai, Ponpat, et alARTICLE328 DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction
2021-11Car crash detection using ensemble deep learning and multimodal data from dashboard camerasChoi, Jae Gyeong; Kong, Chan Woo; Kim, Gyeongho, et alARTICLE346 Car crash detection using ensemble deep learning and multimodal data from dashboard cameras
2021-09A Multimodal Deep Learning-Based Fault Detection Model for a Plastic Injection Molding ProcessKim, Gyeongho; Choi, Jae Gyeong; Ku, Minjoo, et alARTICLE197 A Multimodal Deep Learning-Based Fault Detection Model for a Plastic Injection Molding Process
2021-02A Stacking-Based Deep Neural Network Approach for Effective Network Anomaly DetectionTama, Bayu Adhi; Lim, SunghoonARTICLE376 A Stacking-Based Deep Neural Network Approach for Effective Network Anomaly Detection
2021-02Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluationTama, Bayu Adhi; Lim, SunghoonARTICLE269 Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation
2020-10A Comparative Performance Evaluation of Classification Algorithms for Clinical Decision Support SystemsTama, Bayu Adhi; Lim, SunghoonARTICLE355 A Comparative Performance Evaluation of Classification Algorithms for Clinical Decision Support Systems
2020-05A Multi-Objective Differential Evolutionary Method for Constrained Crowd Judgment AnalysisChatterjee, Sujoy; Lim, SunghoonARTICLE588 A Multi-Objective Differential Evolutionary Method for Constrained Crowd Judgment Analysis
2020-03인공지능 기반의 자동차사고 감지 시스템 적용 사례 분석최재경; 공찬우; 임성훈ARTICLE129 인공지능 기반의 자동차사고 감지 시스템 적용 사례 분석
2019-09Mining Twitter data for causal links between tweets and real-world outcomesLim, Sunghoon; Tucker, Conrad S.ARTICLE581 Mining Twitter data for causal links between tweets and real-world outcomes
2018-09A semantic network model for measuring engagement and performance in online learning platformsLim, Sunghoon; Tucker, Conrad S.; Jablokow, Kathryn, et alARTICLE727 A semantic network model for measuring engagement and performance in online learning platforms
2018-06Automated Discovery of Product Feature Inferences Within Large-Scale Implicit Social Media DataTuarob, Suppawong; Lim, Sunghoon; Tucker, Conrad S.ARTICLE702 Automated Discovery of Product Feature Inferences Within Large-Scale Implicit Social Media Data
2017-11Mitigating Online Product Rating Biases Through the Discovery of Optimistic, Pessimistic, and Realistic ReviewersLim, Sunghoon; Tucker, Conrad S.ARTICLE725 Mitigating Online Product Rating Biases Through the Discovery of Optimistic, Pessimistic, and Realistic Reviewers
2017-02An unsupervised machine learning model for discovering latent infectious diseases using social media dataLim, Sunghoon; Tucker, Conrad S.; Kumara, SoundarARTICLE625 An unsupervised machine learning model for discovering latent infectious diseases using social media data

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