A virtual metrology system for semiconductor manufacturing P Kang, H Lee, S Cho, D Kim, J Park, CK Park, S Doh Expert Systems with Applications 36 (10), 12554-12561, 2009 | 147 | 2009 |
Machine learning-based novelty detection for faulty wafer detection in semiconductor manufacturing D Kim, P Kang, S Cho, H Lee, S Doh Expert Systems with Applications 39 (4), 4075-4083, 2012 | 136 | 2012 |
Virtual metrology for run-to-run control in semiconductor manufacturing P Kang, D Kim, H Lee, S Doh, S Cho Expert Systems with Applications 38 (3), 2508-2522, 2011 | 136 | 2011 |
Semi–supervised support vector regression based on self–training with label uncertainty: An application to virtual metrology in semiconductor manufacturing P Kang, D Kim, S Cho Expert Systems with Applications 51, 85-106, 2016 | 108 | 2016 |
Response modeling with support vector regression D Kim, H Lee, S Cho Expert Systems with Applications 34 (2), 1102-1108, 2008 | 56 | 2008 |
Efficient Feature Selection based on Random Forward Search for Virtual Metrology Modeling S Kang, D Kim, S Cho IEEE Transactions on Semiconductor Manufacturing 24 (9), 391-398, 2016 | 38 | 2016 |
OBGAN: Minority oversampling near borderline with generative adversarial networks W Jo, D Kim Expert Systems with Applications 197, 116694, 2022 | 32 | 2022 |
Pattern selection for support vector regression based response modeling D Kim, S Cho Expert Systems with Applications 39 (10), 8975-8985, 2012 | 18 | 2012 |
Expected margin–based pattern selection for support vector machines D Kim, S Kang, S Cho Expert Systems with Applications 139, 112865, 2020 | 17 | 2020 |
ε-Tube Based Pattern Selection for Support Vector Machines D Kim, S Cho Advances in Knowledge Discovery and Data Mining: 10th Pacific-Asia …, 2006 | 16 | 2006 |
Improvement of virtual metrology performance by removing metrology noises in a training dataset D Kim, P Kang, S Lee, S Kang, S Doh, S Cho Pattern Analysis and Applications 18 (1), 173-189, 2015 | 15 | 2015 |
Depressed Mood Prediction of Elderly People with a Wearable Band J Choi, S Lee, S Kim, D Kim, H Kim Sensors 22 (11), 4174, 2022 | 14 | 2022 |
Solar event detection using deep-learning-based object detection methods JH Baek, S Kim, S Choi, J Park, J Kim, W Jo, D Kim Solar Physics 296 (11), 160, 2021 | 13 | 2021 |
Effect of Irrelevant Variables on Faulty Wafer Detection in Semiconductor Manufacturing D Kim, S Kang Energies 12 (13), 2530, 2019 | 12 | 2019 |
Intracranial Pressure Patterns and Neurological Outcomes in Out-of-Hospital Cardiac Arrest Survivors after Targeted Temperature Management: A Retrospective Observational Study H Song, C Kang, J Park, Y You, Y In, J Min, W Jeong, Y Cho, H Ahn, ... Journal of Clinical Medicine 10 (23), 5697, 2021 | 11 | 2021 |
ICT-based comprehensive health and social-needs assessment system for supporting person-centered community care M Park, EJ Choi, M Jeong, N Lee, M Kwak, M Lee, EC Lim, H Nam, D Kim, ... Healthcare Informatics Research 25 (4), 338-343, 2019 | 10 | 2019 |
Approximate training of one-class support vector machines using expected margin S Kang, D Kim, S Cho Computers & Industrial Engineering 130, 772-778, 2019 | 9 | 2019 |
Evaluating the reliability level of virtual metrology results for flexible process control: a novelty detection-based approach P Kang, D Kim, S Cho Pattern Analysis and Applications 17, 863-881, 2014 | 9 | 2014 |
Neural additive time-series models: Explainable deep learning for multivariate time-series prediction W Jo, D Kim Expert Systems with Applications 228, 120307, 2023 | 8* | 2023 |
Rapid fault cause identification in surface mount technology processes based on factory-wide data analysis D Kim, J Koo, H Kim, S Kang, SH Lee, JT Kang International Journal of Distributed Sensor Networks 15 (2), 1550147719832802, 2019 | 7 | 2019 |