Prof. Changgyun Kim, Department of Artificial Intelligence & Software/Samcheok,South Korea
Changgyun Kim is an esteemed academic and researcher associated with Kangwon National University, Department of Artificial Intelligence & Software, and Dongguk University’s Industrial Engineering department in South Korea. His research expertise spans deep learning, healthcare, and data mining. He has made significant contributions to the field, including developing AI-based systems for detecting betting anomalies in sports, diagnosing tooth-related diseases using panoramic images, and creating models for obesity diagnosis using 3D body information. His work is published in renowned journals such as Scientific Reports, Annals of Applied Sport Science, JMIR Medical Informatics, Sensors, Sustainability, the International Journal of Distributed Sensor Networks, and Applied Sciences. Dr. Kim’s notable projects include establishing IoT-based smart factories for SMEs in Korea and developing web applications for obesity diagnosis using data mining methodologies. His extensive research portfolio underscores his commitment to advancing AI applications in various domains
Professional Profile:
ORCID
Education
No specific details about Changgyun Kim’s educational background are provided in the provided information. To give a more comprehensive overview, details such as degrees obtained, institutions attended, and fields of study would be needed.
Work Experience
- Dongguk University: Jung-gu, Seoul, KR
- Department: Industrial Engineering
- Position: Not specified in the provided information.
- Kangwon National University
- Department: Artificial Intelligence & Software
- Position: Not specified in the provided information.
Publication top Notes:
AI-based betting anomaly detection system to ensure fairness in sports and prevent illegal gambling
Detectability of Sports Betting Anomalies Using Deep Learning-based ResNet: Utilization of K-League Data in South Korea
Tooth-Related Disease Detection System Based on Panoramic Images and Optimization Through Automation: Development Study
Development of an Obesity Information Diagnosis Model Reflecting Body Type Information Using 3D Body Information Values
Development of a Web Application Based on Human Body Obesity Index and Self-Obesity Diagnosis Model Using the Data Mining Methodology
Establishment of an IoT-based smart factory and data analysis model for the quality management of SMEs die-casting companies in Korea