| Surrogate-assisted retinal OCT image classification based on convolutional neural networks Y Rong, D Xiang, W Zhu, K Yu, F Shi, Z Fan, X Chen IEEE journal of biomedical and health informatics 23 (1), 253-263, 2018 | 103 | 2018 |
| Genetic U-Net: automatically designed deep networks for retinal vessel segmentation using a genetic algorithm J Wei, G Zhu, Z Fan, J Liu, Y Rong, J Mo, W Li, X Chen IEEE Transactions on Medical Imaging 41 (2), 292-307, 2021 | 66 | 2021 |
| Optic disk detection in fundus image based on structured learning Z Fan, Y Rong, X Cai, J Lu, W Li, H Lin, X Chen IEEE journal of biomedical and health informatics 22 (1), 224-234, 2017 | 61 | 2017 |
| Accurate retinal vessel segmentation via octave convolution neural network Z Fan, J Mo, B Qiu, W Li, G Zhu, C Li, J Hu, Y Rong, X Chen arXiv preprint arXiv:1906.12193, 2019 | 35 | 2019 |
| Deriving external forces via convolutional neural networks for biomedical image segmentation Y Rong, D Xiang, W Zhu, F Shi, E Gao, Z Fan, X Chen Biomedical optics express 10 (8), 3800-3814, 2019 | 27 | 2019 |
| Real-time prediction of the daily incidence of COVID-19 in 215 countries and territories using machine learning: model development and validation Y Peng, C Li, Y Rong, CP Pang, X Chen, H Chen Journal of Medical Internet Research 23 (6), e24285, 2021 | 25 | 2021 |
| Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning Y Peng, C Li, Y Rong, X Chen, H Chen Journal of global health 10 (2), 2020 | 24 | 2020 |
| Automated blood vessel segmentation of fundus images using region features of vessels Z Fan, J Lu, Y Rong 2016 IEEE Symposium Series on Computational Intelligence (SSCI), 1-6, 2016 | 22 | 2016 |
| Automated blood vessel segmentation in fundus image based on integral channel features and random forests Z Fan, Y Rong, J Lu, J Mo, F Li, X Cai, T Yang 2016 12th World Congress on Intelligent Control and Automation (WCICA), 2063 …, 2016 | 13 | 2016 |
| Multi-objective evolutionary algorithms embedded with machine learning—A survey Z Fan, K Hu, F Li, Y Rong, W Li, H Lin 2016 IEEE Congress on Evolutionary Computation (CEC), 1262-1266, 2016 | 11 | 2016 |
| Tobacco plant recognizing and counting based on svm H Xie, Z Fan, W Li, Y Rong, Y Xiao, L Zhao 2016 International Conference on Industrial Informatics-Computing Technology …, 2016 | 8 | 2016 |
| Segmentation of retinal vessels in fundus images based on U-Net with self-calibrated convolutions and spatial attention modules YB Rong, Y Xiong, C Li, Y Chen, P Wei, C Wei, Z Fan Medical & Biological Engineering & Computing 61 (7), 1745-1755, 2023 | 5 | 2023 |
| Modified hilbert curve for rectangles and cuboids and its application in entropy coding for image and video compression Y Rong, X Zhang, J Lin Entropy 23 (7), 836, 2021 | 4 | 2021 |
| Detecting optic disk based on adaboost and active geometric shape model Z Fan, F Li, Y Rong, W Li, X Cai, H Lin 2015 IEEE International Conference on Cyber Technology in Automation …, 2015 | 4 | 2015 |
| Searchmorph: Multi-scale correlation iterative network for deformable registration X Fan, S Zhuang, Z Zhuang, Y Yuan, S Qiu, ANJ Raj, Y Rong arXiv preprint arXiv:2206.13076, 2022 | 2 | 2022 |
| Direct estimation of choroidal thickness in optical coherence tomography images with convolutional neural networks Y Rong, Z Jiang, W Wu, Q Chen, C Wei, Z Fan, H Chen Journal of Clinical Medicine 11 (11), 3203, 2022 | 2 | 2022 |
| Detecting optic disk based on structured learning Z Fan, Y Rong, X Cai, W Li, H Lin, Z Yu, J Lu 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO), 1127 …, 2015 | 2 | 2015 |
| Slimming Convolutional Neural Network Based on Attention Mechanism for Pavement Crack Detection W Huang, G Zhu, Z Fan, W Li, Y Rong, Y Cai 2021 IEEE 11th Annual International Conference on CYBER Technology in …, 2021 | 1 | 2021 |
| Explaining Convolutional Neural Networks for Area Estimation of Choroidal Neovascularization via Genetic Programming Y Rong, K Yu, D Xiang, W Zhu, Z Fan, X Chen Computational Pathology and Ophthalmic Medical Image Analysis: First …, 2018 | 1 | 2018 |
| Regional choroidal thickness estimation from color fundus images based on convolutional neural networks Y Rong, Q Chen, Z Jiang, Z Fan, H Chen Heliyon, 2024 | | 2024 |
