Accuracy Improvement Technique for Timing Application of LORAN-C Signal. - Sung Hoon Yang; Chang Bok Lee; Young Kyu Lee; Jong Koo Lee; Young Jae Kim; Sang Jeong Lee (IEEE Trans. Instrum. Meas., 2011)

Body Fat Assessment Method Using CT Images with Separation Mask Algorithm. - Young Jae Kim; Seung Hyun Lee; Tae Yun Kim; Jeongyun Park; Seung Hong Choi; Kwang Gi Kim (J. Digit. Imaging, 2013)

RF performance of InGaAs-based T-gate junctionless field-effect transistors which applicable for high frequency network systems. - Jae Hwa Seo; Young Jun Yoon; Sung Yoon Kim; Young Jae Kim; In Man Kang (ICOIN, 2015)

Brain Hologram Visualization for Diagnosis of Tumors using Graphic Imaging. - Jenie Nam; Young Jae Kim; Seung Hyun Lee; Kwang Gi Kim (J. Multim. Inf. Syst., 2016)

Study of profit model of web-dramas on portal sites using big data; Focused on the Web-dramas with the K-pop Singers as the Lead Casts: "EXO, Next Door" and "I Order You". - Se Jong Oh; Young Jae Kim; Ill Chul Doo (Multim. Tools Appl., 2017)

Automated Segmentation Methods of Drusen to Diagnose Age-Related Macular Degeneration Screening in Retinal Images. - Young Jae Kim; Kwang Gi Kim (Comput. Math. Methods Medicine, 2018)

Development and Validation of Segmentation Method for Lung Cancer Volumetry on Chest CT. - Young Jae Kim; Seung Hyun Lee; Kun Young Lim; Kwang Gi Kim (J. Digit. Imaging, 2018)

Novel Sperm Sorting Microfluidic Chip With Feedback Channel and Vertical Orientation. - Young Jae Kim; Kukjin Chun (IEEE SENSORS, 2019)

Lensless Imaging Sensor Kit for Sperm Counting with Microfluidic Chip. - Young Jae Kim; Kukjin Chun (SAS, 2019)

Address Block Counting Using Two-Tier Cardinality Estimation. - Myungkeun Yoon 001; Young Jae Kim (IEEE Access, 2019)

The Effect of CT Scan Parameters on the Measurement of CT Radiomic Features: A Lung Nodule Phantom Study. - Young Jae Kim; Hyun-Ju Lee; Kwang Gi Kim; Seung Hyun Lee (Comput. Math. Methods Medicine, 2019)

A framework of Multi Linear Regression based on Fuzzy Theory and Situation Awareness and its application to Beach Risk Assessment. - Gun-Yoon Shin; Sung-Sam Hong; Dong-Wook Kim; Cheol-Hun Hwang; Myung-Mook Han; Hwayoung Kim; Young Jae Kim (KSII Trans. Internet Inf. Syst., 2020)

Deep learning-based brain metastatic detection and treatment response assessment system on 3D MRI. - Ye Rang Park; Young Jae Kim; Kwang Gi Kim (ICTC, 2021)

Deep vein thrombosis detection based on deep learning for CT images. - Jae Won Seo; Young Jae Kim; Kwang Gi Kim (ICTC, 2021)

Finding Critical Files from a Packet. - JunNyung Hur; Hahoon Jeon; Hyeon Gy Shon; Young Jae Kim; MyungKeun Yoon 001 (INFOCOM, 2021)

Automated Vertebral Segmentation and Measurement of Vertebral Compression Ratio Based on Deep Learning in X-Ray Images. - Dong Hyun Kim; Jin Gyo Jeong; Young Jae Kim; Kwang Gi Kim; Ji Young Jeon (J. Digit. Imaging, 2021)

Comparison of Pre-processed Brain Tumor MR Images Using Deep Learning Detection Algorithms. - Hee Jae Kwon; Gi Pyo Lee; Young Jae Kim; Kwang Gi Kim (J. Multim. Inf. Syst., 2021)

Automatic measurement algorithm of femoral/tibial torsion on standardized CT slices. - Ji Soo Jeon; Young Jae Kim; Kwang Gi Kim (ICTC, 2022)

A Study on Liver Segments Separation and Hologram Visualization Using Deep Learning-Based Liver Vascular in CT Images. - Dae Jin Kim; Young Jae Kim; Youngbae Jeon; Jeong-Heum Baek; Kwang Gi Kim (ICTC, 2022)

Automatic polyp detection using SmartEndo-Net based on fusion feature pyramid network with mix-up edges. - Young Jae Kim; Sohyun Byun; Chung il Ahn; Sangwook Cho; Kwang Gi Kim (Computer-Aided Diagnosis, 2022)

Computer-Aided Diagnosis for Determining Sagittal Spinal Curvatures Using Deep Learning and Radiography. - Hyo Min Lee; Young Jae Kim; Je Bok Cho; Ji Young Jeon; Kwang Gi Kim (J. Digit. Imaging, 2022)

Machine Learning Model Based on Radiomic Features for Differentiation between COVID-19 and Pneumonia on Chest X-ray. - Young Jae Kim (Sensors, 2022)

RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model. - Yoon Ji Kim; Woong Ju; Kye Hyun Nam; Soo Nyung Kim; Young Jae Kim; Kwang Gi Kim (Sensors, 2022)

FILM: Filtering and Machine Learning for Malware Detection in Edge Computing. - Young Jae Kim; Chan-Hyeok Park; MyungKeun Yoon 001 (Sensors, 2022)

Development and Validation of a Multimodal-Based Prognosis and Intervention Prediction Model for COVID-19 Patients in a Multicenter Cohort. - Jeonghoon Lee 001; Jong Seok Ahn; Myung Jin Chung; Yeon Joo Jeong; Jin Hwan Kim; Jae Kwang Lim; Jin Young Kim; Young Jae Kim; Jong Eun Lee; Eun Young Kim (Sensors, 2022)

Segmentation Performance Comparison Considering Regional Characteristics in Chest X-ray Using Deep Learning. - Hyo Min Lee; Young Jae Kim; Kwang Gi Kim (Sensors, 2022)

A Study on 3D Deep Learning-Based Automatic Diagnosis of Nasal Fractures. - Yu Jin Seol; Young Jae Kim; Yoon Sang Kim; Young Woo Cheon; Kwang Gi Kim (Sensors, 2022)

The Development of an Automatic Rib Sequence Labeling System on Axial Computed Tomography Images with 3-Dimensional Region Growing. - Yu Jin Seol; So Hyun Park; Young Jae Kim; Young-Taek Park; Hee Young Lee; Kwang Gi Kim (Sensors, 2022)

Packet Chunking for File Detection. - JunNyung Hur; Hyeon Gy Shon; Young Jae Kim; Myungkeun Yoon 001 (IEEE/ACM Trans. Netw., 2023)

Automatic Spine Segmentation and Parameter Measurement for Radiological Analysis of Whole-Spine Lateral Radiographs Using Deep Learning and Computer Vision. - Yong-Tae Kim; Tae Seok Jeong; Young Jae Kim; Woo Seok Kim; Kwang Gi Kim; Gi Taek Yee (J. Digit. Imaging, 2023)

Non-invasive stroke diagnosis using speech data from dysarthria patients. - Sae Byeol Mun; Young Jae Kim; Kwang Gi Kim (EMBC, 2024)

Comparative Analysis of Brain Tumor Image Segmentation Performance of 2D U-Net and 3D U-Nets with Alternative Normalization Methods. - Tae Joon Kim; Young Jae Kim; Kwang Gi Kim (J. Multim. Inf. Syst., 2024)

Deep Learning-Based Multi-Class Segmentation of the Paranasal Sinuses of Sinusitis Patients Based on Computed Tomographic Images. - Jongwook Whangbo; Juhui Lee; Young Jae Kim; Seon Tae Kim; Kwang Gi Kim (Sensors, 2024)

Deep Learning-Based Nystagmus Detection for BPPV Diagnosis. - Sae Byeol Mun; Young Jae Kim; Ju Hyoung Lee; Gyu Cheol Han; Sung Ho Cho; Seok Jin; Kwang Gi Kim (Sensors, 2024)