Baek Hwan Cho - researchr alias

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Viewing Publication 1 - 22 from 22

2026

Uncertainty-Aware Selective Prediction of Neovascular Age-Related Macular Degeneration Recurrence Using Artificial IntelligenceWon Tae Yoon, Hun-Gyeom Kim, Junhyung Moon 0001, Dat Ngo, Jae Hui Kim, Baek Hwan Cho. access, 14:36453-36468, 2026. [doi]

2022

Semi-supervised automatic seizure detection using personalized anomaly detecting variational autoencoder with behind-the-ear EEGSungmin You, Baek Hwan Cho, Young-Min Shon, Dae-Won Seo, In-Young Kim. cmpb, 213:106542, 2022. [doi]

2021

Automatic stenosis recognition from coronary angiography using convolutional neural networksJong Hak Moon, Da Young Lee, Won Chul Cha, Myung Jin Chung, Kyu-Sung Lee, Baek Hwan Cho, Jin Ho Choi. cmpb, 198:105819, 2021. [doi]

2020

Unsupervised automatic seizure detection for focal-onset seizures recorded with behind-the-ear EEG using an anomaly-detecting generative adversarial networkSungmin You, Baek Hwan Cho, Soon-Hyung Yook, Joo-Young Kim, Young-Min Shon, Dae-Won Seo, In-Young Kim. cmpb, 193:105472, 2020. [doi]

2019

Development of an automatic muscle atrophy measuring algorithm to calculate the ratio of supraspinatus in supraspinous fossa using deep learningJoo-Young Kim, Kyunghan Ro, Sungmin You, Bo Rum Nam, Sunhyun Yook, Hee Seol Park, Jae Chul Yoo, Eunkyoung Park, Kyeongwon Cho, Baek Hwan Cho, In-Young Kim. cmpb, 182, 2019. [doi]

2018

Movement state classification for bimanual BCI from non-human primate's epidural ECoG using three-dimensional convolutional neural networkHoseok Choi, Jeyeon Lee, Jinsick Park, Baek Hwan Cho, Kyoung-Min Lee, Dong Pyo Jang. bci3 2018: 1-3 [doi]

2016

Performance improvement of deep learning based gesture recognition using spatiotemporal demosaicing techniquePaul K. J. Park, Baek Hwan Cho, Jin Man Park, Kyoobin Lee, Ha-Young Kim, Hyo Ah Kang, Hyun-Goo Lee, Jooyeon Woo, Yohan Roh, Won-Jo Lee, Chang-Woo Shin, Qiang Wang, Hyunsurk Ryu. icip 2016: 1624-1628 [doi]

2014

2013

Fast microcalcification detection in ultrasound images using image enhancement and threshold adjacency statisticsBaek Hwan Cho, Chu-Ho Chang, Jong Ha Lee, Eun-Young Ko, Yeong Kyeong Seong, Kyoung-Gu Woo. micad 2013: [doi]

Learning a Structured Graphical Model with Boosted Top-Down Features for Ultrasound Image SegmentationZhihui Hao, Qiang Wang, Xiaotao Wang, Jung-Bae Kim, Youngkyoo Hwang, Baek Hwan Cho, Ping Guo, Won Ki Lee. miccai 2013: 227-234 [doi]

Multiobjective evolutionary optimization for tumor segmentation of breast ultrasound imagesYe-Hoon Kim, Baek Hwan Cho, Yeong Kyeong Seong, Moon Ho Park, JungHoe Kim, Sinsang Yu, Kyoung-Gu Woo. embc 2013: 3650-3653 [doi]

Tumor Subtype-Specific Parameter Optimization in a Hybrid Active Surface Model for Hepatic Tumor Segmentation of 3D Liver UltrasonogramsMyungeun Lee, Jong Hyo Kim, Moon Ho Park, Ye-Hoon Kim, Yeong Kyeong Seong, JungHoe Kim, Baek Hwan Cho, Sinsang Yu, Kyoung-Gu Woo. miccai 2013: 251-258 [doi]

Computer-aided lesion diagnosis in B-mode ultrasound by border irregularity and multiple sonographic featuresJong Ha Lee, Yeong Kyeong Seong, Chu-Ho Chang, Eun-Young Ko, Baek Hwan Cho, Jeonghun Ku, Kyoung-Gu Woo. micad 2013: [doi]

2009

VRIFA: a nonlinear SVM visualization tool using nomogram and localized radial basis function (LRBF) kernelsNgo Anh Vien, Nguyen Hoang Viet, TaeChoong Chung, Hwanjo Yu, SungChul Kim, Baek Hwan Cho. CIKM 2009: 2081-2082 [doi]

2008

2007

Pattern classification using principal components of cortical thickness and its discriminative pattern in schizophreniaUicheul Yoon, Jong-Min Lee, Kiho Im, Yong-Wook Shin, Baek Hwan Cho, In-Young Kim, Jun Soo Kwon, Sun I. Kim. neuroimage, 34(4):1405-1415, 2007. [doi]

2004

Neurofeedback Training with Virtual Reality for Inattention and ImpulsivenessBaek Hwan Cho, Saebyul Kim, Dong Ik Shin, Jang-Han Lee, Sang Min Lee, In-Young Kim, Sun I. Kim. cbsn, 7(5):519-526, 2004. [doi]

2002

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