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Biography and Research Information
OverviewAI-generated summary
Jonghoon Lee's research interests span advancements in semiconductor devices, artificial intelligence, and agricultural technology. He has co-authored publications on high-density 3D-NAND flash memory, focusing on aspects such as write throughput and interface speeds. His work also extends to the application of AI in diverse fields, including the prediction of biological age using clinical biomarkers, the enhancement of crop-weed recognition through unsupervised domain adaptation, and the development of AI-based network security for 5G industrial IoT environments. Lee has also investigated the use of unmanned aerial vehicles for preliminary structural safety assessments of buildings and explored intelligent visual servoing for precise agricultural tasks like watermelon pollination. His research portfolio includes work on multi-scale temporal variational autoencoders for anomaly detection in multivariate time series and pixel-level image segmentation algorithms. Lee holds a h-index of 15 and has authored 90 publications, which have been cited 875 times.
Metrics
- h-index: 15
- Publications: 90
- Citations: 883
Selected Publications
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Antitrust and corporate taxation (2025)
Collaboration Network
Top Collaborators
Hyongsuk Kim
Jeonbuk National University (KR)
8 shared publications
- Overcoming field variability: unsupervised domain adaptation for enhanced crop-weed recognition in diverse farmlands
- Accurate and robust pollinations for watermelons using intelligence guided visual servoing
- A pixel-level coarse-to-fine image segmentation labelling algorithm
- CWD30: A new benchmark dataset for crop weed recognition in precision agriculture
- CWD30: A new benchmark dataset for crop weed recognition in precision agriculture
Showing 5 of 8 shared publications
Talha Ilyas
Jeonbuk National University (KR)
5 shared publications
- Overcoming field variability: unsupervised domain adaptation for enhanced crop-weed recognition in diverse farmlands
- Accurate and robust pollinations for watermelons using intelligence guided visual servoing
- A pixel-level coarse-to-fine image segmentation labelling algorithm
- CWD30: A new benchmark dataset for crop weed recognition in precision agriculture
- Adaptive Deep Learning for Crop Weed Discrimination in Unseen Fields
Jong‐Geun Park
Electronics and Telecommunications Research Institute (KR)
4 shared publications
- AI-based Network Security Enhancement for 5G Industrial Internet of Things Environments
- Network Anomaly Detection based on GAN with Scaling Properties
- Network Anomaly Detection based on Domain Adaptation for 5G Network Security
- Multivariate Time Series Anomaly Detection with Deep Learning Models Leveraging Inter-Variable Relationships
Okjae Won
Rural Development Administration (KR)
4 shared publications
- Overcoming field variability: unsupervised domain adaptation for enhanced crop-weed recognition in diverse farmlands
- A pixel-level coarse-to-fine image segmentation labelling algorithm
- CWD30: A new benchmark dataset for crop weed recognition in precision agriculture
- Adaptive Deep Learning for Crop Weed Discrimination in Unseen Fields
Hyunjin Kim
Electronics and Telecommunications Research Institute (KR)
3 shared publications
- AI-based Network Security Enhancement for 5G Industrial Internet of Things Environments
- Network Anomaly Detection based on GAN with Scaling Properties
- Network Anomaly Detection based on Domain Adaptation for 5G Network Security
Dewa Made Sri Arsa
Udayana University (ID)
3 shared publications
- CWD30: A new benchmark dataset for crop weed recognition in precision agriculture
- Deep Learning for Weeds’ Growth Point Detection based on U-Net
- An Autonomous Weeding Robot with Novel Unsupervised Domain Adaptation
Tuan-Anh Pham
Green Cross (South Korea) (KR)
3 shared publications
- MST-VAE: Multi-Scale Temporal Variational Autoencoder for Anomaly Detection in Multivariate Time Series
- TransSentLog: Interpretable Anomaly Detection Using Transformer and Sentiment Analysis on Individual Log Event
- Lightweight Multi-Task Learning Method for System Log Anomaly Detection
Cheol-Hee Park
Electronics and Telecommunications Research Institute (KR)
2 shared publications
- Network Anomaly Detection based on GAN with Scaling Properties
- Network Anomaly Detection based on Domain Adaptation for 5G Network Security
Chul‐Young Bae
2 shared publications
- Comparison of Biological Age Prediction Models Using Clinical Biomarkers Commonly Measured in Clinical Practice Settings: AI Techniques Vs. Traditional Statistical Methods
- A Study on Survival Analysis Methods Using Neural Network to Prevent Cancers
Yongchae Jeong
Jeonbuk National University (KR)
2 shared publications
- Overcoming field variability: unsupervised domain adaptation for enhanced crop-weed recognition in diverse farmlands
- Adaptive Deep Learning for Crop Weed Discrimination in Unseen Fields
Khubaib Ahmad
Jeonbuk National University (KR)
2 shared publications
- Accurate and robust pollinations for watermelons using intelligence guided visual servoing
- An Autonomous Weeding Robot with Novel Unsupervised Domain Adaptation
Yoori Im
1 shared publication
- Comparison of Biological Age Prediction Models Using Clinical Biomarkers Commonly Measured in Clinical Practice Settings: AI Techniques Vs. Traditional Statistical Methods
Choong-Shik Park
1 shared publication
- Comparison of Biological Age Prediction Models Using Clinical Biomarkers Commonly Measured in Clinical Practice Settings: AI Techniques Vs. Traditional Statistical Methods
Mi-Young Kim
1 shared publication
- Comparison of Biological Age Prediction Models Using Clinical Biomarkers Commonly Measured in Clinical Practice Settings: AI Techniques Vs. Traditional Statistical Methods
Hojeong Kwon
New York University (US)
1 shared publication
- Comparison of Biological Age Prediction Models Using Clinical Biomarkers Commonly Measured in Clinical Practice Settings: AI Techniques Vs. Traditional Statistical Methods
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