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ORCIDSeokho Kang 0001
Person information
- affiliation: Sungkyunkwan University, Suwon, Korea
Other persons with the same name
- Seokho Kang 0002 — Korea University School of Medicine, Seoul, Korea
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2020 – today
- 2024
[j56]Hyungu Kang, Jeongmin Hong, Jiwon Lee, Seokho Kang
:
Photovoltaic Cell Defect Detection Based on Weakly Supervised Learning With Module-Level Annotations. IEEE Access 12: 5575-5583 (2024)- [j55]Yoonhyung Lee, Seokho Kang:
Dynamic ensemble of regression neural networks based on predictive uncertainty. Comput. Ind. Eng. 190: 110011 (2024) - [j54]Myeonginn Kang, Seokho Kang:
Knowledge distillation with insufficient training data for regression. Eng. Appl. Artif. Intell. 132: 108001 (2024) - [j53]Sunbin Lee, Seokho Kang:
Training-free approach to constructing ensemble of local experts. Expert Syst. Appl. 257: 125072 (2024) - [j52]Jongmin Han, Youngchun Kwon, Youn-Suk Choi, Seokho Kang:
Improving chemical reaction yield prediction using pre-trained graph neural networks. J. Cheminformatics 16(1): 25 (2024) - [j51]Jeongmin Hong, Seokho Kang:
Score distillation for anomaly detection. Knowl. Based Syst. 295: 111842 (2024) - [c2]Eugene Yang, Hao Chen, Seokho Kang:
Mixup Your Own Latent: Efficient and Robust Self-Supervised Learning on Small Images. ECAI 2024: 3163-3170 - 2023
- [j50]Jisu Yoo, Seokho Kang:
Class-Adaptive Data Augmentation for Image Classification. IEEE Access 11: 26393-26402 (2023) - [j49]Myeonginn Kang, Seokho Kang:
Surrogate approach to uncertainty quantification of neural networks for regression. Appl. Soft Comput. 139: 110234 (2023) - [j48]Hyungu Kang, Seokho Kang:
Semi-supervised rotation-invariant representation learning for wafer map pattern analysis. Eng. Appl. Artif. Intell. 120: 105864 (2023) - [j47]Youngjae Bae, Seokho Kang:
Supervised contrastive learning for wafer map pattern classification. Eng. Appl. Artif. Intell. 126(Part D): 107154 (2023) - [j46]Jaewoong Shim, Seokho Kang:
Learning from single-defect wafer maps to classify mixed-defect wafer maps. Expert Syst. Appl. 233: 120923 (2023) - [j45]Jongwook Son, Seokho Kang:
Efficient improvement of classification accuracy via selective test-time augmentation. Inf. Sci. 642: 119148 (2023) - [j44]Jongmin Han, Seokho Kang:
Optimization of missing value imputation for neural networks. Inf. Sci. 649: 119668 (2023) - 2022
- [j43]Suhee Yoon, Seokho Kang:
Semi-automatic wafer map pattern classification with convolutional neural networks. Comput. Ind. Eng. 166: 107977 (2022) - [j42]Jaewoong Shim, Seokho Kang:
Domain-adaptive active learning for cost-effective virtual metrology modeling. Comput. Ind. 135: 103572 (2022) - [j41]Seokho Kang:
Using binary classifiers for one-class classification. Expert Syst. Appl. 187: 115920 (2022) - [j40]Kyoham Shin, Seokho Kang:
ADANOISE: Training neural networks with adaptive noise for imbalanced data classification. Expert Syst. Appl. 192: 116364 (2022) - [j39]Jongmin Han, Seokho Kang:
Dynamic imputation for improved training of neural network with missing values. Expert Syst. Appl. 194: 116508 (2022) - [j38]Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Seokho Kang:
Uncertainty-aware prediction of chemical reaction yields with graph neural networks. J. Cheminformatics 14(1): 2 (2022) - [j37]Youngchun Kwon, Sun Kim, Youn-Suk Choi, Seokho Kang:
Generative Modeling to Predict Multiple Suitable Conditions for Chemical Reactions. J. Chem. Inf. Model. 62(23): 5952-5960 (2022) - 2021
- [j36]Jaeho Kim, Seokho Kang:
Model-Agnostic Post-Processing Based on Recursive Feedback for Medical Image Segmentation. IEEE Access 9: 157035-157042 (2021) - [j35]Hyungu Kang, Seokho Kang:
A stacking ensemble classifier with handcrafted and convolutional features for wafer map pattern classification. Comput. Ind. 129: 103450 (2021) - [j34]Myeonginn Kang, Seokho Kang:
Data-free knowledge distillation in neural networks for regression. Expert Syst. Appl. 175: 114813 (2021) - [j33]Jaewoong Shim, Seokho Kang, Sungzoon Cho:
Active cluster annotation for wafer map pattern classification in semiconductor manufacturing. Expert Syst. Appl. 183: 115429 (2021) - [j32]Kyoham Shin, Jongmin Han, Seokho Kang:
MI-MOTE: Multiple imputation-based minority oversampling technique for imbalanced and incomplete data classification. Inf. Sci. 575: 80-89 (2021) - [j31]Jongmin Han, Seokho Kang:
Active learning with missing values considering imputation uncertainty. Knowl. Based Syst. 224: 107079 (2021) - [j30]Seokho Kang:
Product failure prediction with missing data using graph neural networks. Neural Comput. Appl. 33(12): 7225-7234 (2021) - 2020
- [j29]Seokho Kang:
Rotation-Invariant Wafer Map Pattern Classification With Convolutional Neural Networks. IEEE Access 8: 170650-170658 (2020) - [j28]Hwehee Chung, Jongho Park, Jongsoo Keum, Hongdo Ki, Seokho Kang:
Unsupervised Anomaly Detection Using Style Distillation. IEEE Access 8: 221494-221502 (2020) - [j27]Dongil Kim, Seokho Kang, Sungzoon Cho:
Expected margin-based pattern selection for support vector machines. Expert Syst. Appl. 139 (2020) - [j26]Seokho Kang:
Model validation failure in class imbalance problems. Expert Syst. Appl. 146: 113190 (2020) - [j25]Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Kyoham Shin, Seokho Kang:
Compressed graph representation for scalable molecular graph generation. J. Cheminformatics 12(1): 58 (2020) - [j24]Youngchun Kwon, Dongseon Lee, Youn-Suk Choi, Myeonginn Kang, Seokho Kang:
Neural Message Passing for NMR Chemical Shift Prediction. J. Chem. Inf. Model. 60(4): 2024-2030 (2020) - [j23]Seokho Kang, Youngchun Kwon, Dongseon Lee, Youn-Suk Choi:
Predictive Modeling of NMR Chemical Shifts without Using Atomic-Level Annotations. J. Chem. Inf. Model. 60(8): 3765-3769 (2020) - [j22]Seokho Kang:
Joint modeling of classification and regression for improving faulty wafer detection in semiconductor manufacturing. J. Intell. Manuf. 31(2): 319-326 (2020) - [c1]Jaewoong Shim, Seokho Kang, Sungzoon Cho:
Kernel Rotation Forests for Classification. BigComp 2020: 406-409
2010 – 2019
- 2019
- [j21]Seokho Kang, Dongil Kim, Sungzoon Cho:
Approximate training of one-class support vector machines using expected margin. Comput. Ind. Eng. 130: 772-778 (2019) - [j20]Dongil Kim, Jeongin Koo, Hyein Kim, Seokho Kang, Sang-Hyun Lee, Jeong-Tae Kang:
Rapid fault cause identification in surface mount technology processes based on factory-wide data analysis. Int. J. Distributed Sens. Networks 15(2) (2019) - [j19]Youngchun Kwon, Jiho Yoo, Youn-Suk Choi, Wonjoon Song, Dongseon Lee, Seokho Kang:
Efficient learning of non-autoregressive graph variational autoencoders for molecular graph generation. J. Cheminformatics 11(1): 70:1-70:10 (2019) - [j18]Seokho Kang, Kyunghyun Cho:
Conditional Molecular Design with Deep Generative Models. J. Chem. Inf. Model. 59(1): 43-52 (2019) - [j17]Jaehong Yu, Seokho Kang:
Clustering-based proxy measure for optimizing one-class classifiers. Pattern Recognit. Lett. 117: 37-44 (2019) - [i2]Elman Mansimov, Omar Mahmood, Seokho Kang, Kyunghyun Cho:
Molecular geometry prediction using a deep generative graph neural network. CoRR abs/1904.00314 (2019) - 2018
- [j16]Seokho Kang:
Personalized prediction of drug efficacy for diabetes treatment via patient-level sequential modeling with neural networks. Artif. Intell. Medicine 85: 1-6 (2018) - [j15]Youngdoo Son, Seokho Kang:
Regression with re-labeling for noisy data. Expert Syst. Appl. 114: 578-587 (2018) - [j14]Seokho Kang, Eunji Kim, Jaewoong Shim, Wonsang Chang, Sungzoon Cho:
Product failure prediction with missing data. Int. J. Prod. Res. 56(14): 4849-4859 (2018) - [j13]Seokho Kang, Pilsung Kang:
Locally linear ensemble for regression. Inf. Sci. 432: 199-209 (2018) - [i1]Seokho Kang, Kyunghyun Cho:
Conditional molecular design with deep generative models. CoRR abs/1805.00108 (2018) - 2017
- [j12]Seokho Kang, Eunji Kim, Jaewoong Shim, Sungzoon Cho, Wonsang Chang, Junhwan Kim:
Mining the relationship between production and customer service data for failure analysis of industrial products. Comput. Ind. Eng. 106: 137-146 (2017) - [j11]Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho, Jee Su Park:
Virtual metrology for copper-clad laminate manufacturing. Comput. Ind. Eng. 109: 280-287 (2017) - [j10]Jiwon Yang, Seung-kyung Lee, Seokho Kang, Sungzoon Cho, Young-Hak Lee, Hae-Sang Park:
Ranking process parameter association with low yield wafers using spec-out event network analysis. Comput. Ind. Eng. 113: 419-424 (2017) - [j9]Seokho Kang, Sungzoon Cho, Su-jin Rhee, Kyung-Sang Yu:
Reliable prediction of anti-diabetic drug failure using a reject option. Pattern Anal. Appl. 20(3): 883-891 (2017) - 2015
- [j8]Seokho Kang, Sungzoon Cho, Pilsung Kang:
Multi-class classification via heterogeneous ensemble of one-class classifiers. Eng. Appl. Artif. Intell. 43: 35-43 (2015) - [j7]Seokho Kang, Pilsung Kang, Taehoon Ko, Sungzoon Cho, Su-jin Rhee, Kyung-Sang Yu:
An efficient and effective ensemble of support vector machines for anti-diabetic drug failure prediction. Expert Syst. Appl. 42(9): 4265-4273 (2015) - [j6]Seokho Kang, Sungzoon Cho:
A novel multi-class classification algorithm based on one-class support vector machine. Intell. Data Anal. 19(4): 713-725 (2015) - [j5]Seokho Kang, Sungzoon Cho, Pilsung Kang:
Constructing a multi-class classifier using one-against-one approach with different binary classifiers. Neurocomputing 149: 677-682 (2015) - [j4]Seokho Kang, Sungzoon Cho:
Optimal construction of one-against-one classifier based on meta-learning. Neurocomputing 167: 459-466 (2015) - [j3]Dongil Kim, Pilsung Kang, Seung-kyung Lee, Seokho Kang, Seungyong Doh, Sungzoon Cho:
Improvement of virtual metrology performance by removing metrology noises in a training dataset. Pattern Anal. Appl. 18(1): 173-189 (2015) - 2014
- [j2]Seung-kyung Lee, Bongseok Kim, Minhoe Huh, Jooseoung Park, Seokho Kang, Sungzoon Cho, Dongha Lee, Daehyung Lee:
Knowledge discovery in inspection reports of marine structures. Expert Syst. Appl. 41(4): 1153-1167 (2014) - [j1]Seokho Kang, Sungzoon Cho:
Approximating support vector machine with artificial neural network for fast prediction. Expert Syst. Appl. 41(10): 4989-4995 (2014)
Coauthor Index
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