| Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models HY Kim, CH Won Expert Systems with Applications 103, 25-37, 2018 | 666 | 2018 |
| ModAugNet: A new forecasting framework for stock market index value with an overfitting prevention LSTM module and a prediction LSTM module Y Baek, HY Kim Expert Systems with Applications 113, 457-480, 2018 | 339 | 2018 |
| Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data T Kim, HY Kim PloS one 14 (2), e0212320, 2019 | 329 | 2019 |
| Learning representations for the early detection of sepsis with deep neural networks HJ Kam, HY Kim Computers in biology and medicine 89, 248-255, 2017 | 218 | 2017 |
| Improving financial trading decisions using deep Q-learning: Predicting the number of shares, action strategies, and transfer learning G Jeong, HY Kim Expert Systems with Applications 117, 125-138, 2019 | 181 | 2019 |
| Stock market forecasting with super-high dimensional time-series data using ConvLSTM, trend sampling, and specialized data augmentation SW Lee, HY Kim expert systems with applications 161, 113704, 2020 | 91 | 2020 |
| Method and apparatus for supporting diagnosis of region of interest by providing comparison image HY Kim, HJ Kam, YH Kim US Patent 9,959,622, 2018 | 79 | 2018 |
| Early forecasting of rice blast disease using long short-term memory recurrent neural networks Y Kim, JH Roh, HY Kim Sustainability 10 (1), 34, 2017 | 78 | 2017 |
| Stock market forecasting using a multi-task approach integrating long short-term memory and the random forest framework HJ Park, Y Kim, HY Kim Applied Soft Computing 114, 108106, 2022 | 65 | 2022 |
| Model training method and apparatus, and data recognizing method H Kang, H Kim US Patent 10,410,114, 2019 | 61 | 2019 |
| Estimating compressive strength of concrete using deep convolutional neural networks with digital microscope images Y Jang, Y Ahn, HY Kim Journal of Computing in Civil Engineering 33 (3), 04019018, 2019 | 53 | 2019 |
| Optimizing the pairs-trading strategy using deep reinforcement learning with trading and stop-loss boundaries T Kim, HY Kim Complexity 2019, 1-20, 2019 | 45 | 2019 |
| Method and apparatus for high-dimensional data visualization H Kim, HM Park, H Park, C Jae-Gul US Patent 9,508,167, 2016 | 40 | 2016 |
| Computer-aided diagnosis apparatus and method HJ Kam, HY Kim, JH Jeon US Patent 9,662,040, 2017 | 37 | 2017 |
| Bshapenet: Object detection and instance segmentation with bounding shape masks BR Kang, H Lee, K Park, H Ryu, HY Kim Pattern Recognition Letters 131, 449-455, 2020 | 36 | 2020 |
| MultiDefectNet: Multi-class defect detection of building façade based on deep convolutional neural network K Lee, G Hong, L Sael, S Lee, HY Kim Sustainability 12 (22), 9785, 2020 | 33 | 2020 |
| Performance improvement of deep learning based gesture recognition using spatiotemporal demosaicing technique PKJ Park, BH Cho, JM Park, K Lee, HY Kim, HA Kang, HG Lee, J Woo, ... 2016 IEEE International Conference on Image Processing (ICIP), 1624-1628, 2016 | 33 | 2016 |
| Apparatus and method for visualizing anatomical elements in a medical image BH Cho, YK Seong, YH Kim, HY Kim, JH Jeon US Patent 10,383,602, 2019 | 27 | 2019 |
| Digital vision based concrete compressive strength evaluating model using deep convolutional neural network HK Shin, YH Ahn, SH Lee, HY Kim CMC-COMPUTERS MATERIALS & CONTINUA 61 (2), 911-928, 2019 | 24 | 2019 |
| Automatic concrete damage recognition using multi-level attention convolutional neural network HK Shin, YH Ahn, SH Lee, HY Kim Materials 13 (23), 5549, 2020 | 21 | 2020 |
