Yangwon LEE

Professor

Pusan National University

South Korea

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About

Yangwon LEE is a Professor at Pukyong National University in South Korea. His research areas include semantic segmentation in imaging, flood inundation assessment, wireless sensor networks, IoT applications for farm surveillance, and the use of AI and deep learning in agricultural yield predictions. Professor LEE has published extensively on topics such as disaster monitoring and satellite imagery analysis, reflecting his expertise in environmental and agricultural sciences.

Articles (25)

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2022

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2022

Collaborators (5)

A. S. M. Sanwar Hosen

Assistant Professor

Woosong University

SOUTH KOREA

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Seung Hee Kim

Chapman University

UNITED STATES

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Ki-Hong Park

Pusan National University

SOUTH KOREA

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Jaeil Cho

Associate Professor

Chonnam National University

SOUTH KOREA

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Byung-Seo Kim

Hongik University

SOUTH KOREA

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Yangwon LEE

Research Interests

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About

Articles (25)

Real-Time Farm Surveillance Using IoT and YOLOv8 for Animal Intrusion Detection

An Adaptive 24 GHz PSO-Based Optimized VCO in Next-Generation Wireless Sensor Networks

Semantic Segmentation of Fire Fronts in Helicopter Imagery Using Vision Transformer Models

Estimation of Flood Inundation Area Using Soil Moisture Active Passive Fractional Water Data with an LSTM Model

AI- and Deep Learning-Powered Driver Drowsiness Detection Method Using Facial Analysis

An Automated Machine Learning Approach to the Retrieval of Daily Soil Moisture in South Korea Using Satellite Images, Meteorological Data, and Digital Elevation Model

Dual Features, Compact Dimensions and X-Band Applications for the Design and Fabrication of Annular Circular Ring-Based Crescent-Moon-Shaped Microstrip Patch Antenna

Single-Temporal Sentinel-2 for Analyzing Burned Area Detection Methods: A Study of 14 Cases in Republic of Korea Considering Land Cover

A Reformed PSO-Based High Linear Optimized Up-Conversion Mixer for Radar Application

AI-Based Paddy Rice Yield Prediction Using Satellite Images, Meteorological Data, and Digital Elevation Model: Case Study of South Korea, 2000–2023

Correlation-Based Evaluation of GEMS Satellite Products Using Environmental and Meteorological Measurements

Dataset Construction and Semantic Segmentation of Buildings and Roads from CAS500-1 Images

Development of Administrative District-Based Water Body Monitoring System Using Sentinel-1 SAR and Swin Transformer in South Korea

Landslide Detection Using Swin Transformer Model and PlanetScope Images: A Performance Comparison by the Input Data Combination

Real-Time Retrieval of Daily Soil Moisture Using IMERG and GK2A Satellite Images with NWP and Topographic Data: A Machine Learning Approach for South Korea

Estimation of High-Resolution Soil Moisture in Canadian Croplands Using Deep Neural Network with Sentinel-1 and Sentinel-2 Images

Evaluation of the Robustness of an AutoML Model for Paddy Rice Yields under Extreme Weather Conditions

Front-End Development for Radar Applications: A Focus on 24 GHz Transmitter Design

A Comparative Study on the Object Detection of Deposited Marine Debris (DMD) Using YOLOv5 and YOLOv7 Models

A Real-time Correction of the Underestimation Noise for GK2A Daily NDVI

Analysis of Burned Areas in North Korea Using Satellite-based Wildfire Damage Indices

Cloud Detection from Sentinel-2 Images Using DeepLabV3+ and Swin Transformer Models

Detection of Active Fire Objects from Drone Images Using YOLOv7x Model

Detection of Marine Oil Spills from PlanetScope Images Using DeepLabV3+ Model

Flood Detection from Sentinel-1 SAR Images using U-Net and HRNetV2 Models

Collaborators (5)

A. S. M. Sanwar Hosen

Seung Hee Kim

Ki-Hong Park

Jaeil Cho

Byung-Seo Kim

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