The Characterization of a Forest Cover through Shape and Texture Parameters from Quickbird Imagery. - Choen Kim; Sung-Hoo Hong (IGARSS (3), 2008)

Self-Attentive Normalization for Automated Gleason Grading System. - Hong-Kyu Shin; Sung-Hoo Hong; Yeong-Jin Choi; Yong-Goo Shin; Seung Park; Sung-Jea Ko (TENCON, 2020)

Machine learning-based prediction model for late recurrence after surgery in patients with renal cell carcinoma. - Hyung Min Kim 003; Seok-Soo Byun; Jung Kwon Kim; Chang Wook Jeong; Cheol Kwak; Eu Chang Hwang; Seokho Kang 002; Jinsoo Chung; Yong-June Kim; Yun-Sok Ha; Sung-Hoo Hong (BMC Medical Informatics Decis. Mak., 2022)

A Unified Multi-Phase CT Synthesis and Classification Framework for Kidney Cancer Diagnosis With Incomplete Data. - Kwang-Hyun Uhm; Seung-Won Jung; Moon Hyung Choi; Sung-Hoo Hong; Sung-Jea Ko (IEEE J. Biomed. Health Informatics, 2022)

Exploring 3D U-Net Training Configurations and Post-processing Strategies for the MICCAI 2023 Kidney and Tumor Segmentation Challenge. - Kwang-Hyun Uhm; Hyunjun Cho; Zhixin Xu; Seohoon Lim; Seung-Won Jung; Sung-Hoo Hong; Sung-Jea Ko (KiTS@MICCAI, 2023)

Lesion-aware cross-phase attention network for renal tumor subtype classification on multi-phase CT scans. - Kwang-Hyun Uhm; Seung-Won Jung; Sung-Hoo Hong; Sung-Jea Ko (Comput. Biol. Medicine, 2024)

Machine learning models for predicting the onset of chronic kidney disease after surgery in patients with renal cell carcinoma. - Seol Whan Oh; Seok-Soo Byun; Jung Kwon Kim; Chang Wook Jeong; Cheol Kwak; Eu Chang Hwang; Seokho Kang 002; Jinsoo Chung; Yong-June Kim; Yun-Sok Ha; Sung-Hoo Hong (BMC Medical Informatics Decis. Mak., 2024)