DistressNet: a wireless ad hoc and sensor network architecture for situation management in disaster response SM George, W Zhou, H Chenji, M Won, YO Lee, A Pazarloglou, R Stoleru, ... IEEE Communications Magazine 48 (3), 128-136, 2010 | 342 | 2010 |
Application of deep neural network and generative adversarial network to industrial maintenance: A case study of induction motor fault detection YO Lee, J Jo, J Hwang Big Data (Big Data), 2017 IEEE International Conference on, 2017 | 180 | 2017 |
CEGAN: Classification Enhancement Generative Adversarial Networks for unraveling data imbalance problems S Suh, H Lee, P Lukowicz, YO Lee Neural Networks 133, 69-86, 2021 | 97 | 2021 |
Generalized multiscale feature extraction for remaining useful life prediction of bearings with generative adversarial networks S Suh, P Lukowicz, YO Lee Knowledge-Based Systems 237, 107866, 2022 | 76 | 2022 |
Generative oversampling method for imbalanced data on bearing fault detection and diagnosis S Suh, H Lee, J Jo, P Lukowicz, YO Lee Applied Sciences 9 (4), 746, 2019 | 64 | 2019 |
Prediction performance of an artificial neural network model for the amount of cooling energy consumption in hotel rooms JW Moon, SK Jung, YO Lee, S Choi Energies 8 (8), 8226-8243, 2015 | 39 | 2015 |
Two-stage generative adversarial networks for binarization of color document images S Suh, J Kim, P Lukowicz, YO Lee Pattern Recognition 130, 108810, 2022 | 30 | 2022 |
Predicting chemical properties using self-attention multi-task learning based on SMILES representation S Lim, YO Lee 2020 25th International Conference on Pattern Recognition (ICPR), 3146-3153, 2021 | 27 | 2021 |
Supervised health stage prediction using convolutional neural networks for bearing wear S Suh, J Jang, S Won, MS Jha, YO Lee Sensors 20 (20), 5846, 2020 | 27 | 2020 |
Discriminative feature generation for classification of imbalanced data S Suh, P Lukowicz, YO Lee Pattern Recognition 122, 108302, 2022 | 24 | 2022 |
COVID-19 through adverse outcome pathways: Building networks to better understand the disease–3rd CIAO AOP design workshop LA Clerbaux, N Amigó, MJ Amorim, A Bal-Price, SB Leite, A Beronius, ... Altex 39 (2), 322–335, 2022 | 22 | 2022 |
Robust shipping label recognition and validation for logistics by using deep neural networks S Suh, H Lee, YO Lee, P Lukowicz, J Hwang 2019 IEEE International Conference on Image Processing (ICIP), 4509-4513, 2019 | 22 | 2019 |
Constructing disjoint paths for failure recovery and multipath routing YO Lee, ALN Reddy Computer Networks 56 (2), 719-730, 2012 | 22 | 2012 |
Two-stage generative adversarial networks for document image binarization with color noise and background removal S Suh, J Kim, P Lukowicz, YO Lee arXiv preprint arXiv:2010.10103, 2020 | 16 | 2020 |
Fusion of global-local features for image quality inspection of shipping label S Suh, P Lukowicz, YO Lee 2020 25th International Conference on Pattern Recognition (ICPR), 2643-2649, 2021 | 13 | 2021 |
Disjoint multi-path routing and failure recovery YO Lee, ALN Reddy 2010 IEEE International Conference on Communications, 1-6, 2010 | 13 | 2010 |
Supervised segmentation with domain adaptation for small sampled orbital CT images S Suh, S Cheon, W Choi, YW Chung, WK Cho, JS Paik, SE Kim, ... Journal of Computational Design and Engineering 9 (2), 783-792, 2022 | 12 | 2022 |
Acute Adverse Effects of Metallic Nanomaterials on Cardiac and Behavioral Changes in Daphnia magna J Park, C Park, Y Lee, C Ryu, J Park, Y Kim Environments 9 (2), 26, 2022 | 11 | 2022 |
Multi-Layer Nested Scatter Plot: a Data Wrangling Method for Correlated Multi-Channel Time Series Signals J Jo, YO Lee, J Hwang 2018 First International Conference on Artificial Intelligence for …, 2019 | 9 | 2019 |
The Effect of Resampling on Data‐Imbalanced Conditions for Prediction towards Nuclear Receptor Profiling Using Deep Learning YJK Yong Oh Lee Molecular Informatics, 2020 | 8 | 2020 |