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강원대학교 로고
강원대학교 로고

Current member

Ph.D. Candidates

Hong-Gu Lee

Hong-Gu Lee

Ph.D. Candidate
Research Area: - AI-driven Beekeeping Systems
- Computer Vision & AI
- Hyperspectral Imaging Applications
Current Research Topic: - Disease and pest detection in honeybees using hyperspectral imaging, computer vision and Deep learning
- Development of digitization system, precision AI models, LLMs services for honeybee ecology, behavioral research
- Fruit quality assessment and grading models using hyperspectral imaging
- Soil monitoring device and system
- Intelligent system for tree seedling selection
- Development of a device for measuring leaf moisture content based on optical technology
- Analysis of crop data cultivated in space environments
Publication list: - Enhancing Bee Mite Detection with YOLO The Role of Data Augmentation and Stratified Sampling
- Identifying an Image-Processing Method for Detection of Bee Mite in Honey Bee Based on Keypoint Analysis
- (Patent) 꿀벌 응애 및 병해충 검출을 위한 측정 장치
- (Patent) 꿀벌 응애 인식을 위한 영상 데이터 처리 방법 및 이를 이 용한 꿀벌 응애 검출 방법
- (Patent) 산물벼의 품질 측정 장치
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Doojin Song

Doojin Song

Ph.D. Candidate
Research Area: Non-destructive Sensing, Hyperspectral Imaging Applications
Current Research Topic: - Determination of quality of agricultural products using spectroscopy and hyperspectral light, Determination for Smart APC
Publication list: - Performance Improvement of Partial Least Squares Regression Soluble Solid Content Prediction Model Based on Adjusting Distance between Light Source and Spectral Sensor according to Apple Size
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Seung-woo Chun

Seung-woo Chun

Ph.D. Candidate
Research Area: Hyperspectral Imaging Applications, AI, Image Processing
Current Research Topic: - Development of AI model for post-harvest safety and quality assessment of fresh produce
- Development of Early Detection Technology for Strawberry Gray Mold Infection Using Hyperspectral Fluorescence Imaging
- The development of AI-based fresh fruit and vegetable quality determination technology
- Development of Non-contact Fuel Moisture Measurement Device Based on Optical Sensors
- Development of a smart farming integrated management system for paddy crops (rice, wheat, garlic, onion, potato)
Publication list: [1] Chun, S. W., et al. (2024). Deep learning algorithm development for early detection of Botrytis cinerea infected strawberry fruit...
[2] 천승우, et al. (2025). 로봇팔 제어 정확도 향상을 위한 다차원 영상센서기반 인식 객체의 3 차원 측위 알고리즘 연구...
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Researcher

Ha-Eun Yang

Ha-Eun Yang (양하은)

Researcher
Research Area: - Near-Infrared Spectroscopy (NIRS)
- Machine Learning & Deep Learning for Agricultural Applications
- Nondestructive Quality Assessment of Rice
- Real-time Sensing System Development for Combine Harvesters
Current Research Topic: - Enhancement and On-site Implementation of Rice Farming Automation Package Technology
- Field Demonstration of AI Solution for Real-time Rice Harvesting and Quality Assessment
Publication list: - (SCI) Prediction of protein content in paddy rice (Oryza sativa L.) combining near-infrared spectroscopy and deep-learning algorithm
- (SCI) Development of Deep Learning and Machine Learning Models for Predicting Moisture Content
- (patent) 산물벼의 품질 측정 장치(Rice Grain Quality Measurement Device)
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Master Candidates

Jeong-Yong Shin

Jeong-Yong Shin

Master Candidate
Research Area: Digital Beekeeping, Non-destructive Sensing, Object Detection, Device design
Current Research Topic: - Development of digital management technology for pest of Varroa Destructor and Vespa for climate change adaption
- Building Big Data on Beekeeping Environments and Standardizing Digital Beekeeping Management
- Development of AI-based technology for predicting bee pest and disease
- Development of a smart farming integrated management system for paddy crops (rice, wheat, garlic, onion, potato)
- Demonstration of AI Solution for Simultaneous Quality Measurement During Rice Harvesting
- Soil-CAM
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Woo-hyeong Yu

Woo-hyeong Yu

Master Candidate
Research Area: Hyperspectral Imaging Applications Image Processing, E-noses
Current Research Topic: - Development of Non-destructive Fruit Quality Assessment and Development of Lettuce Phytotoxicity Evaluation Technology
- Development of Early Detection Technology for Vegetable Stress in Space Environment Dragon Cultivation
- Development of AI model for post-harvest safety and quality assessment of fresh produce
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Jeongwoo Han

Jeongwoo Han

Master Candidate
Research Area: Hyperspectral Imaging Applications, AI, Image Processing
Current Research Topic: - The development of AI-based fresh fruit and vegetable quality determination technology
- Development of Digital-based Phenotyping Measurement and Analysis System for Forest Seedlings
- Development of AI model for post-harvest safety and quality assessment of fresh produce
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Undergraduate Interns

Woon-tak Han

Woon-tak Han

Undergraduate Intern
Research Area: Hyperspectral Imaging Applications, AI, Device design
Current Research Topic: Development of Smart Beehive
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