Seokho Kang

According to our database, Seokho Kang authored at least 54 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Improving chemical reaction yield prediction using pre-trained graph neural networks.

Jongmin Han, Youngchun Kwon, Youn-Suk Choi, Seokho Kang

J. Cheminformatics, December, 2024

Photovoltaic Cell Defect Detection Based on Weakly Supervised Learning With Module-Level Annotations.

Hyungu Kang, Jeongmin Hong, Jiwon Lee, Seokho Kang

IEEE Access, 2024

2023

Learning from single-defect wafer maps to classify mixed-defect wafer maps.

Jaewoong Shim, Seokho Kang

Expert Syst. Appl., December, 2023

Optimization of missing value imputation for neural networks.

Jongmin Han, Seokho Kang

Inf. Sci., November, 2023

Supervised contrastive learning for wafer map pattern classification.

Youngjae Bae, Seokho Kang

Eng. Appl. Artif. Intell., November, 2023

Surrogate approach to uncertainty quantification of neural networks for regression.

Myeonginn Kang, Seokho Kang

Appl. Soft Comput., May, 2023

Semi-supervised rotation-invariant representation learning for wafer map pattern analysis.

Hyungu Kang, Seokho Kang

Eng. Appl. Artif. Intell., April, 2023

Efficient improvement of classification accuracy via selective test-time augmentation.

Jongwook Son, Seokho Kang

Inf. Sci., 2023

Class-Adaptive Data Augmentation for Image Classification.

Jisu Yoo, Seokho Kang

IEEE Access, 2023

2022

Generative Modeling to Predict Multiple Suitable Conditions for Chemical Reactions.

Youngchun Kwon, Sun Kim, Youn-Suk Choi, Seokho Kang

J. Chem. Inf. Model., 2022

Uncertainty-aware prediction of chemical reaction yields with graph neural networks.

Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Seokho Kang

J. Cheminformatics, 2022

ADANOISE: Training neural networks with adaptive noise for imbalanced data classification.

Kyoham Shin, Seokho Kang

Expert Syst. Appl., 2022

Using binary classifiers for one-class classification.

Seokho Kang

Expert Syst. Appl., 2022

Dynamic imputation for improved training of neural network with missing values.

Jongmin Han, Seokho Kang

Expert Syst. Appl., 2022

Domain-adaptive active learning for cost-effective virtual metrology modeling.

Jaewoong Shim, Seokho Kang

Comput. Ind., 2022

Semi-automatic wafer map pattern classification with convolutional neural networks.

Suhee Yoon, Seokho Kang

Comput. Ind. Eng., 2022

2021

Product failure prediction with missing data using graph neural networks.

Seokho Kang

Neural Comput. Appl., 2021

Active learning with missing values considering imputation uncertainty.

Jongmin Han, Seokho Kang

Knowl. Based Syst., 2021

MI-MOTE: Multiple imputation-based minority oversampling technique for imbalanced and incomplete data classification.

Kyoham Shin, Jongmin Han, Seokho Kang

Inf. Sci., 2021

Active cluster annotation for wafer map pattern classification in semiconductor manufacturing.

Jaewoong Shim, Seokho Kang, Sungzoon Cho

Expert Syst. Appl., 2021

Data-free knowledge distillation in neural networks for regression.

Myeonginn Kang, Seokho Kang

Expert Syst. Appl., 2021

A stacking ensemble classifier with handcrafted and convolutional features for wafer map pattern classification.

Hyungu Kang, Seokho Kang

Comput. Ind., 2021

Model-Agnostic Post-Processing Based on Recursive Feedback for Medical Image Segmentation.

Jaeho Kim, Seokho Kang

IEEE Access, 2021

2020

Joint modeling of classification and regression for improving faulty wafer detection in semiconductor manufacturing.

Seokho Kang

J. Intell. Manuf., 2020

Neural Message Passing for NMR Chemical Shift Prediction.

Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Myeonginn Kang, Seokho Kang

J. Chem. Inf. Model., 2020

Predictive Modeling of NMR Chemical Shifts without Using Atomic-Level Annotations.

Seokho Kang, Youngchun Kwon, Dongseon Lee, Youn-Suk Choi

J. Chem. Inf. Model., 2020

Compressed graph representation for scalable molecular graph generation.

Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Kyoham Shin, Seokho Kang

J. Cheminformatics, 2020

Expected margin-based pattern selection for support vector machines.

Dongil Kim, Seokho Kang, Sungzoon Cho

Expert Syst. Appl., 2020

Model validation failure in class imbalance problems.

Seokho Kang

Expert Syst. Appl., 2020

Rotation-Invariant Wafer Map Pattern Classification With Convolutional Neural Networks.

Seokho Kang

IEEE Access, 2020

Unsupervised Anomaly Detection Using Style Distillation.

Hwehee Chung, Jongho Park, Jongsoo Keum, Hongdo Ki, Seokho Kang

IEEE Access, 2020

Kernel Rotation Forests for Classification.

Jaewoong Shim, Seokho Kang, Sungzoon Cho

Proceedings of the 2020 IEEE International Conference on Big Data and Smart Computing, 2020

2019

Clustering-based proxy measure for optimizing one-class classifiers.

Jaehong Yu, Seokho Kang

Pattern Recognit. Lett., 2019

Conditional Molecular Design with Deep Generative Models.

Seokho Kang, Kyunghyun Cho

J. Chem. Inf. Model., 2019

Efficient learning of non-autoregressive graph variational autoencoders for molecular graph generation.

Youngchun Kwon, Jiho Yoo, Youn-Suk Choi, Wonjoon Song, Dongseon Lee, Seokho Kang

J. Cheminformatics, 2019

Rapid fault cause identification in surface mount technology processes based on factory-wide data analysis.

Dongil Kim, Jeongin Koo, Hyein Kim, Seokho Kang, Sang-Hyun Lee, Jeong-Tae Kang

Int. J. Distributed Sens. Networks, 2019

Molecular geometry prediction using a deep generative graph neural network.

Elman Mansimov, Omar Mahmood, Seokho Kang, Kyunghyun Cho

CoRR, 2019

Approximate training of one-class support vector machines using expected margin.

Seokho Kang, Dongil Kim, Sungzoon Cho

Comput. Ind. Eng., 2019

2018

Locally linear ensemble for regression.

Seokho Kang, Pilsung Kang

Inf. Sci., 2018

Product failure prediction with missing data.

Seokho Kang, Eunji Kim, Jaewoong Shim, Wonsang Chang, Sungzoon Cho

Int. J. Prod. Res., 2018

Regression with re-labeling for noisy data.

Youngdoo Son, Seokho Kang

Expert Syst. Appl., 2018

Personalized prediction of drug efficacy for diabetes treatment via patient-level sequential modeling with neural networks.

Seokho Kang

Artif. Intell. Medicine, 2018

2017

Reliable prediction of anti-diabetic drug failure using a reject option.

Seokho Kang, Sungzoon Cho, Su-jin Rhee, Kyung-Sang Yu

Pattern Anal. Appl., 2017

Ranking process parameter association with low yield wafers using spec-out event network analysis.

Jiwon Yang, Seung-kyung Lee, Seokho Kang, Sungzoon Cho, Young-Hak Lee, Hae-Sang Park

Comput. Ind. Eng., 2017

Virtual metrology for copper-clad laminate manufacturing.

Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho, Jee Su Park

Comput. Ind. Eng., 2017

Mining the relationship between production and customer service data for failure analysis of industrial products.

Seokho Kang, Eunji Kim, Jaewoong Shim, Sungzoon Cho, Wonsang Chang, Junhwan Kim

Comput. Ind. Eng., 2017

2015

Improvement of virtual metrology performance by removing metrology noises in a training dataset.

Dongil Kim, Pilsung Kang, Seung-kyung Lee, Seokho Kang, Seungyong Doh, Sungzoon Cho

Pattern Anal. Appl., 2015

Constructing a multi-class classifier using one-against-one approach with different binary classifiers.

Seokho Kang, Sungzoon Cho, Pilsung Kang

Neurocomputing, 2015

Optimal construction of one-against-one classifier based on meta-learning.

Seokho Kang, Sungzoon Cho

Neurocomputing, 2015

A novel multi-class classification algorithm based on one-class support vector machine.

Seokho Kang, Sungzoon Cho

Intell. Data Anal., 2015

An efficient and effective ensemble of support vector machines for anti-diabetic drug failure prediction.

Seokho Kang, Pilsung Kang, Taehoon Ko, Sungzoon Cho, Su-jin Rhee, Kyung-Sang Yu

Expert Syst. Appl., 2015

Multi-class classification via heterogeneous ensemble of one-class classifiers.

Seokho Kang, Sungzoon Cho, Pilsung Kang

Eng. Appl. Artif. Intell., 2015

2014

Knowledge discovery in inspection reports of marine structures.

Seung-kyung Lee, Bongseok Kim, Minhoe Huh, Jooseoung Park, Seokho Kang, Sungzoon Cho, Dongha Lee, Daehyung Lee

Expert Syst. Appl., 2014

Approximating support vector machine with artificial neural network for fast prediction.

Seokho Kang, Sungzoon Cho

Expert Syst. Appl., 2014