Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea. - Hyun-Woo Jo; Sujong Lee; Eunbeen Park; Chul-Hee Lim; Cholho Song; Halim Lee; Youngjin Ko; Sungeun Cha; Hoonjoo Yoon; Woo-Kyun Lee (IEEE Trans. Geosci. Remote. Sens., 2020)

Phenological Classification Using Deep Learning and the Sentinel-2 Satellite to Identify Priority Afforestation Sites in North Korea. - Joon Kim; Chul-Hee Lim; Hyun-Woo Jo; Woo-Kyun Lee (Remote. Sens., 2021)

Towards Global Crop Maps with Transfer Learning. - Hyun-Woo Jo; Alkiviadis Koukos; Vasileios Sitokonstantinou; Woo-Kyun Lee; Charalampos Kontoes (CoRR, 2022)

Modeling Historical and Future Forest Fires in South Korea: The FLAM Optimization Approach. - Hyun-Woo Jo; Andrey Krasovskiy; Mina Hong; Shelby Corning; Whijin Kim; Florian Kraxner; Woo-Kyun Lee (Remote. Sens., 2023)

Towards Global Crop Maps with Transfer Learning. - Alkiviadis Koukos; Hyun-Woo Jo; Vasileios Sitokonstantinou; Ilias Tsoumas; Charalampos Kontoes; Woo-Kyun Lee (IGARSS, 2024)

Application of the domain adaptation method using a phenological classification framework for the land-cover classification of North Korea. - Joon Kim; Hyun-Woo Jo; Whijin Kim; Yujeong Jeong; Eunbeen Park; Sujong Lee; Moonil Kim; Woo-Kyun Lee (Ecol. Informatics, 2024)

Projecting Forest Fire Probability in South Korea Under Climate Change, Population, and Forest Management Scenarios Using AI & Process-Based Hybrid Model (FLAM-Net). - Hyun-Woo Jo; Myoung-Soo Won; Florian Kraxner; Seong Woo Jeon; Yowhan Son; Andrey Krasovskiy; Woo-Kyun Lee (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)