ScholarWorks: Researcher Page

BROWSE

ScholarWorks

Researcher Page

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 Date	Title	Author(s)	Type	View	Altmetrics
2022-06	A Deep Learning-based Cryptocurrency Price Prediction Model That Uses On-chain Data	Kim, Gyeongho; Shin, Dong-Hyun; Choi, Jae Gyeong, et al	ARTICLE	228	A Deep Learning-based Cryptocurrency Price Prediction Model That Uses On-chain Data
2022-04	The Charging Infrastructure Design Problem with Electric Taxi Demand Prediction Using Convolutional LSTM	Hwang, Seong Wook; Lim, Sunghoon	ARTICLE	159	The Charging Infrastructure Design Problem with Electric Taxi Demand Prediction Using Convolutional LSTM
2022-04	An EfficientNet-Based Weighted Ensemble Model for Industrial Machine Malfunction Detection Using Acoustic Signals	Tama, Bayu Adhi; Vania, Malinda; Kim, Iljung, et al	ARTICLE	148	An EfficientNet-Based Weighted Ensemble Model for Industrial Machine Malfunction Detection Using Acoustic Signals
2022-04	Development of an Interpretable Maritime Accident Prediction System Using Machine Learning Techniques	Kim, Gyeongho; Lim, Sunghoon	ARTICLE	127	Development of an Interpretable Maritime Accident Prediction System Using Machine Learning Techniques
2022-03	A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning	Chatterjee, Sujoy; Lim, Sunghoon	ARTICLE	149	A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning
2022-02	Characterization of power demand and energy consumption for fused filament fabrication using CFR-PEEK	Kim, Kyudong; Noh, Heena; Park, Kijung, et al	ARTICLE	138	Characterization of power demand and energy consumption for fused filament fabrication using CFR-PEEK
2021-12	A deep learning-based time series model with missing value handling techniques to predict various types of liquid cargo traffic	Lim, Sunghoon; Kim, Sun Jun; Park, YoungJae, et al	ARTICLE	490	A deep learning-based time series model with missing value handling techniques to predict various types of liquid cargo traffic
2021-12	DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction	Tuarob, Suppawong; Wettayakorn, Poom; Phetchai, Ponpat, et al	ARTICLE	328	DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction
2021-11	Car crash detection using ensemble deep learning and multimodal data from dashboard cameras	Choi, Jae Gyeong; Kong, Chan Woo; Kim, Gyeongho, et al	ARTICLE	346	Car crash detection using ensemble deep learning and multimodal data from dashboard cameras
2021-09	A Multimodal Deep Learning-Based Fault Detection Model for a Plastic Injection Molding Process	Kim, Gyeongho; Choi, Jae Gyeong; Ku, Minjoo, et al	ARTICLE	197	A Multimodal Deep Learning-Based Fault Detection Model for a Plastic Injection Molding Process
2021-02	A Stacking-Based Deep Neural Network Approach for Effective Network Anomaly Detection	Tama, Bayu Adhi; Lim, Sunghoon	ARTICLE	376	A Stacking-Based Deep Neural Network Approach for Effective Network Anomaly Detection
2021-02	Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation	Tama, Bayu Adhi; Lim, Sunghoon	ARTICLE	269	Ensemble learning for intrusion detection systems: A systematic mapping study and cross-benchmark evaluation
2020-10	A Comparative Performance Evaluation of Classification Algorithms for Clinical Decision Support Systems	Tama, Bayu Adhi; Lim, Sunghoon	ARTICLE	355	A Comparative Performance Evaluation of Classification Algorithms for Clinical Decision Support Systems
2020-05	A Multi-Objective Differential Evolutionary Method for Constrained Crowd Judgment Analysis	Chatterjee, Sujoy; Lim, Sunghoon	ARTICLE	588	A Multi-Objective Differential Evolutionary Method for Constrained Crowd Judgment Analysis
2020-03	인공지능 기반의 자동차사고 감지 시스템 적용 사례 분석	최재경; 공찬우; 임성훈	ARTICLE	129	인공지능 기반의 자동차사고 감지 시스템 적용 사례 분석
2019-09	Mining Twitter data for causal links between tweets and real-world outcomes	Lim, Sunghoon; Tucker, Conrad S.	ARTICLE	581	Mining Twitter data for causal links between tweets and real-world outcomes
2018-09	A semantic network model for measuring engagement and performance in online learning platforms	Lim, Sunghoon; Tucker, Conrad S.; Jablokow, Kathryn, et al	ARTICLE	727	A semantic network model for measuring engagement and performance in online learning platforms
2018-06	Automated Discovery of Product Feature Inferences Within Large-Scale Implicit Social Media Data	Tuarob, Suppawong; Lim, Sunghoon; Tucker, Conrad S.	ARTICLE	702	Automated Discovery of Product Feature Inferences Within Large-Scale Implicit Social Media Data
2017-11	Mitigating Online Product Rating Biases Through the Discovery of Optimistic, Pessimistic, and Realistic Reviewers	Lim, Sunghoon; Tucker, Conrad S.	ARTICLE	725	Mitigating Online Product Rating Biases Through the Discovery of Optimistic, Pessimistic, and Realistic Reviewers
2017-02	An unsupervised machine learning model for discovering latent infectious diseases using social media data	Lim, Sunghoon; Tucker, Conrad S.; Kumara, Soundar	ARTICLE	625	An unsupervised machine learning model for discovering latent infectious diseases using social media data

1 2

STATISTICS: Total View :17,847,764; Total Download :3,137,512; Today View :438

RSS 1.0 RSS 2.0

BROWSE

Researcher Page

MENU