| Plankton classification on imbalanced large scale database via convolutional neural networks with transfer learning H Lee, M Park, J Kim 2016 IEEE international conference on image processing (ICIP), 3713-3717, 2016 | 223 | 2016 |
| Cephalometric landmark detection in dental x-ray images using convolutional neural networks H Lee, M Park, J Kim Medical imaging 2017: Computer-aided diagnosis 10134, 494-499, 2017 | 91 | 2017 |
| Segmentation of overlapping cervical cells in microscopic images with superpixel partitioning and cell-wise contour refinement H Lee, J Kim Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 82 | 2016 |
| Deep feature classification of angiomyolipoma without visible fat and renal cell carcinoma in abdominal contrast‐enhanced CT images with texture image patches and hand‐crafted … H Lee, H Hong, J Kim, DC Jung Medical physics 45 (4), 1550-1561, 2018 | 80 | 2018 |
| Differentiation of fat‐poor angiomyolipoma from clear cell renal cell carcinoma in contrast‐enhanced MDCT images using quantitative feature classification HS Lee, H Hong, DC Jung, S Park, J Kim Medical physics 44 (7), 3604-3614, 2017 | 67 | 2017 |
| HARRISON: A benchmark on hashtag recommendation for real-world images in social networks M Park, H Li, J Kim arXiv preprint arXiv:1605.05054, 2016 | 33 | 2016 |
| Classification of focal liver lesions in CT images using convolutional neural networks with lesion information augmented patches and synthetic data augmentation H Lee, H Lee, H Hong, H Bae, JS Lim, J Kim Medical physics 48 (9), 5029-5046, 2021 | 21 | 2021 |
| BCD-NET: a novel method for cartilage segmentation of knee MRI via deep segmentation networks with bone-cartilage-complex modeling H Lee, H Hong, J Kim 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 20 | 2018 |
| Segmentation of anterior cruciate ligament in knee MR images using graph cuts with patient-specific shape constraints and label refinement H Lee, H Hong, J Kim Computers in biology and medicine 55, 1-10, 2014 | 20 | 2014 |
| Detection and segmentation of small renal masses in contrast-enhanced CT images using texture and context feature classification HS Lee, H Hong, J Kim 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017 | 15 | 2017 |
| Contextual convolutional neural networks for lung nodule classification using Gaussian-weighted average image patches H Lee, H Lee, M Park, J Kim Medical Imaging 2017: Computer-Aided Diagnosis 10134, 544-550, 2017 | 15 | 2017 |
| Seed growing for interactive image segmentation using SVM classification with geodesic distance S Park, HS Lee, J Kim Electronics Letters 53 (1), 22-24, 2017 | 12 | 2017 |
| Deep Learning in Medical Imaging H Lee, M Park, J Kim The Korean Society of Radiology 20 (1), 13-18, 2014 | 10 | 2014 |
| Anterior cruciate ligament segmentation from knee MR images using graph cuts with geometric and probabilistic shape constraints H Lee, H Hong, J Kim Asian Conference on Computer Vision, 305-315, 2012 | 10 | 2012 |
| Superior prognosis prediction performance of deep learning for gastric cancer compared to Yonsei prognosis prediction model using Cox regression. WJ Hyung, T Son, M Park, H Lee, YN Kim, HI Kim, JW Kim, JH Cheong, ... Journal of Clinical Oncology 35 (4_suppl), 164-164, 2017 | 9 | 2017 |
| Automatic image segmentation using saliency detection and superpixel graph cuts S Kang, H Lee, J Kim, J Kim Robot Intelligence Technology and Applications 2012: An Edition of the …, 2013 | 9 | 2013 |
| Uni-and multi-modal radiomic features for the predicting prostate cancer aggressiveness J Jung, H Hong, H Lee, SI Hwang, HJ Lee 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1-4, 2020 | 7 | 2020 |
| Radiomics analysis of contrast-enhanced CT for classification of hepatic focal lesions in colorectal cancer patients: Its limitations compared to radiologists H Bae, H Lee, S Kim, K Han, H Rhee, D Kim, H Kwon, H Hong, JS Lim European Radiology 31 (11), 8786-8796, 2021 | 6 | 2021 |
| Can deep neural networks match the related objects?: A survey on imagenet-trained classification models HS Lee, H Jung, AA Agarwal, J Kim arXiv preprint arXiv:1709.03806, 2017 | 6 | 2017 |
| Seed growing for interactive image segmentation with geodesic voting S Park, HS Lee, J Kim 2016 IEEE International Conference on Image Processing (ICIP), 2564-2568, 2016 | 6 | 2016 |
Junmo KimSchool of Electrical Engineering, KAISTПотвърден имейл адрес: kaist.ac.kr
