| Going deeper with contextual CNN for hyperspectral image classification H Lee, H Kwon IEEE Transactions on Image Processing 26 (10), 4843-4855, 2017 | 1008 | 2017 |
| Kernel RX-algorithm: A nonlinear anomaly detector for hyperspectral imagery H Kwon, NM Nasrabadi IEEE transactions on Geoscience and Remote Sensing 43 (2), 388-397, 2005 | 908 | 2005 |
| Adaptive anomaly detection using subspace separation for hyperspectral imagery H Kwon, SZ Der, NM Nasrabadi Optical Engineering 42 (11), 3342-3351, 2003 | 204 | 2003 |
| Kernel matched subspace detectors for hyperspectral target detection H Kwon, NM Nasrabadi IEEE transactions on pattern analysis and machine intelligence 28 (2), 178-194, 2005 | 183 | 2005 |
| A rugd dataset for autonomous navigation and visual perception in unstructured outdoor environments M Wigness, S Eum, JG Rogers, D Han, H Kwon 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019 | 166 | 2019 |
| Contextual deep CNN based hyperspectral classification H Lee, H Kwon 2016 IEEE international geoscience and remote sensing symposium (IGARSS …, 2016 | 135 | 2016 |
| Kernel orthogonal subspace projection for hyperspectral signal classification H Kwon, NM Nasrabadi IEEE Transactions on Geoscience and Remote Sensing 43 (12), 2952-2962, 2005 | 116 | 2005 |
| Me r-cnn: Multi-expert r-cnn for object detection H Lee, S Eum, H Kwon IEEE Transactions on Image Processing 29, 1030-1044, 2019 | 104* | 2019 |
| Weakly supervised localization using deep feature maps AJ Bency, H Kwon, H Lee, S Karthikeyan, BS Manjunath Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 102 | 2016 |
| Delving into robust object detection from unmanned aerial vehicles: A deep nuisance disentanglement approach Z Wu, K Suresh, P Narayanan, H Xu, H Kwon, Z Wang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 95 | 2019 |
| Seeing the forest from the trees: A holistic approach to near-infrared heterogeneous face recognition C Reale, NM Nasrabadi, H Kwon, R Chellappa Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 90 | 2016 |
| Clio: Enabling automatic compilation of deep learning pipelines across iot and cloud J Huang, C Samplawski, D Ganesan, B Marlin, H Kwon Proceedings of the 26th Annual International Conference on Mobile Computing …, 2020 | 76 | 2020 |
| A comparative analysis of kernel subspace target detectors for hyperspectral imagery H Kwon, NM Nasrabadi EURASIP Journal on Advances in Signal Processing 2007, 1-13, 2006 | 71 | 2006 |
| Kernel eigenspace separation transform for subspace anomaly detection in hyperspectral imagery H Goldberg, H Kwon, NM Nasrabadi IEEE Geoscience and Remote Sensing Letters 4 (4), 581-585, 2007 | 63 | 2007 |
| Kernel spectral matched filter for hyperspectral imagery H Kwon, NM Nasrabadi International Journal of Computer Vision 71, 127-141, 2007 | 61 | 2007 |
| Single-trial EEG RSVP classification using convolutional neural networks J Shamwell, H Lee, H Kwon, AR Marathe, V Lawhern, W Nothwang Micro-and nanotechnology sensors, systems, and applications VIII 9836, 373-382, 2016 | 52 | 2016 |
| Adaptive multisensor target detection using feature-based fusion H Kwon, SZ Der, NM Nasrabadi Optical Engineering 41 (1), 69-80, 2002 | 52 | 2002 |
| Support-vector-based hyperspectral anomaly detection using optimized kernel parameters P Gurram, H Kwon IEEE Geoscience and Remote Sensing Letters 8 (6), 1060-1064, 2011 | 51 | 2011 |
| Sparse kernel-based hyperspectral anomaly detection P Gurram, H Kwon, T Han IEEE Geoscience and Remote Sensing Letters 9 (5), 943-947, 2012 | 47 | 2012 |
| Sparse kernel-based ensemble learning with fully optimized kernel parameters for hyperspectral classification problems P Gurram, H Kwon IEEE Transactions on Geoscience and Remote Sensing 51 (2), 787-802, 2012 | 43 | 2012 |
