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Charmgil Hong
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2020 – today
- 2025
[c22]Jihyun Moon, Charmgil Hong:
Multimodal Clinical Decision Support for Melanoma Diagnosis Using Retrieval-Augmented Generation and Vision-Language Models. AVSS 2025: 1-6
[c21]Dong Gun Park, Soyeon Park, Chang Ha Lee, Hyunkyoo Choi, Charmgil Hong:
Fine-Grained Video Indexing and Retrieval with Vision-Language Models. AVSS 2025: 1-6
[c20]Charmgil Hong
, Doohee Chung
, Jongyeong Kim
, Heewon Jung
:
Quantum Deepflow: A Quantum-Integrated Forecasting Platform for Strategic Decisions in Raw Material Procurement. CIKM 2025: 6649-6653
[c19]Jihyun Moon, Charmgil Hong
:
Retrieval-Augmented VLMs for Multimodal Melanoma Diagnosis. ISIC@MICCAI 2025: 46-56
[c18]Soyeon Park
, Heeseo Jeong, Soon Sun Kim
, Jae Youn Cheong
, Charmgil Hong
:
Transformer-Based Risk Estimation of HCC in Patients with Chronic Hepatitis B. PRIME@MICCAI 2025: 221-233
[c17]Chongmyung Kwon, Yujin Kim
, Seoeun Park, Yunji Lee, Charmgil Hong
:
MMM: Quantum-Chemical Molecular Representation Learning for Combinatorial Drug Recommendation. PRIME@MICCAI 2025: 234-245
[c16]Harim Kim, Yuhan Wang, Minkyu Ahn, Heeyoul Choi, Yuyin Zhou, Charmgil Hong:
Harnessing EHRs for Diffusion-Based Anomaly Detection on Chest X-Rays. MICCAI (3) 2025: 235-245
[i9]Harim Kim, Yuhan Wang, Minkyu Ahn, Heeyoul Choi, Yuyin Zhou, Charmgil Hong:
Harnessing EHRs for Diffusion-based Anomaly Detection on Chest X-rays. CoRR abs/2505.17311 (2025)
[i8]Jihyun Moon, Charmgil Hong:
Retrieval-Augmented VLMs for Multimodal Melanoma Diagnosis. CoRR abs/2509.08338 (2025)
[i7]Chongmyung Kwon, Yujin Kim, Seoeun Park, Yunji Lee, Charmgil Hong:
MMM: Quantum-Chemical Molecular Representation Learning for Combinatorial Drug Recommendation. CoRR abs/2510.07910 (2025)- 2024
[c15]Harim Kim, Minchae Kim, Taewoo Kim, Kyujin Cho, Charmgil Hong:
AREST: Attention-Based Red-Light Violation Detection for Safety Technology. AVSS 2024: 1-7
[c14]Harim Kim, Chang Ha Lee, Charmgil Hong:
VATMAN: Video Anomaly Transformer for Monitoring Accidents and Nefariousness. AVSS 2024: 1-7
[c13]Harim Kim
, Chang Ha Lee
, Charmgil Hong
:
Transformer for Point Anomaly Detection. CIKM 2024: 1080-1088
[c12]Jaemin Jung, Soonyong Park, Harim Kim, Chang Ha Lee, Charmgil Hong:
Artificial Intelligence-Driven Video Indexing for Rapid Surveillance Footage Summarization and Review. IJCAI 2024: 8687-8690
[c11]Hannah Hyesun Chun, Chanju Lee, Hyunkyoo Choi, Charmgil Hong:
Bridging the Linguistic Divide: Developing a North-South Korean Parallel Corpus for Machine Translation. PACLIC 2024: 801-809- 2023
[c10]Geonyeong Choi, Hyunwoo Yook, Jeong-Woo Han, Charmgil Hong:
AWS: GNNs that Aggregate with Self-node Representation for Dehydrogenation Enthalpy Prediction. ACIIDS (Companion) 2023: 169-180
[c9]Harim Kim, Chang Ha Lee, Charmgil Hong:
Crime Scene Detection in Surveillance Videos Using Variational AutoEncoder-Based Support Vector Data Description. ACIIDS (Companion) 2023: 451-464
[c8]Geonyeong Choi, Hyo Jung Cho, Soon Sun Kim, Ji Eun Han, Jae Youn Cheong, Charmgil Hong:
Drug Induced Liver Injury Prediction with Injective Molecular Transformer. BHI 2023: 1-4- 2021
[i6]Junhyung Kim, Byungyoon Park, Charmgil Hong:
Multi-Scale Label Relation Learning for Multi-Label Classification Using 1-Dimensional Convolutional Neural Networks. CoRR abs/2107.05941 (2021)
2010 – 2019
- 2019
[j2]Gaurav Trivedi
, Charmgil Hong, Esmaeel R. Dadashzadeh, Robert M. Handzel
, Harry Hochheiser
, Shyam Visweswaran:
Identifying incidental findings from radiology reports of trauma patients: An evaluation of automated feature representation methods. Int. J. Medical Informatics 129: 81-87 (2019)- 2018
[c7]Charmgil Hong, Milos Hauskrecht:
Multivariate Conditional Outlier Detection: Identifying Unusual Input-Output Associations in Data. FLAIRS 2018: 176-179- 2017
[i5]Charmgil Hong, Siqi Liu, Milos Hauskrecht:
Detection of Abnormal Input-Output Associations. CoRR abs/1708.01035 (2017)- 2016
[j1]Milos Hauskrecht, Iyad Batal, Charmgil Hong, Quang Nguyen, Gregory F. Cooper, Shyam Visweswaran, Gilles Clermont:
Outlier-based detection of unusual patient-management actions: An ICU study. J. Biomed. Informatics 64: 211-221 (2016)
[c6]Charmgil Hong, Milos Hauskrecht:
Multivariate Conditional Outlier Detection and Its Clinical Application. AAAI 2016: 4216-4217
[i4]Charmgil Hong, Rumi Ghosh, Soundar Srinivasan:
Dealing with Class Imbalance using Thresholding. CoRR abs/1607.02705 (2016)
[i3]Charmgil Hong, Milos Hauskrecht:
Detecting Unusual Input-Output Associations in Multivariate Conditional Data. CoRR abs/1612.07374 (2016)- 2015
[c5]Charmgil Hong, Milos Hauskrecht:
Multivariate Conditional Anomaly Detection and Its Clinical Application. AAAI 2015: 4239-4240
[c4]Charmgil Hong, Iyad Batal, Milos Hauskrecht:
A Generalized Mixture Framework for Multi-label Classification. SDM 2015: 712-720
[i2]Charmgil Hong, Milos Hauskrecht:
MCODE: Multivariate Conditional Outlier Detection. CoRR abs/1505.04097 (2015)- 2014
[c3]Charmgil Hong, Iyad Batal, Milos Hauskrecht:
A Mixtures-of-Trees Framework for Multi-Label Classification. CIKM 2014: 211-220
[c2]Mahdi Pakdaman Naeini, Iyad Batal, Zitao Liu, Charmgil Hong, Milos Hauskrecht:
An Optimization-based Framework to Learn Conditional Random Fields for Multi-label Classification. SDM 2014: 992-1000
[i1]Charmgil Hong, Iyad Batal, Milos Hauskrecht:
A Mixtures-of-Experts Framework for Multi-Label Classification. CoRR abs/1409.4698 (2014)- 2013
[c1]Iyad Batal, Charmgil Hong, Milos Hauskrecht:
An efficient probabilistic framework for multi-dimensional classification. CIKM 2013: 2417-2422
Coauthor Index

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