| Opposition-based learning: a new scheme for machine intelligence HR Tizhoosh International Conference on Computational Intelligence for Modelling …, 2005 | 2737 | 2005 |
| Opposition-based differential evolution S Rahnamayan, HR Tizhoosh, MMA Salama IEEE Transactions on Evolutionary computation 12 (1), 64-79, 2008 | 1991 | 2008 |
| Artificial Intelligence and Digital Pathology: Challenges and Opportunities HR Tizhoosh, L Pantanowitz Journal of Pathology Informatics 9 (38), 2018 | 596 | 2018 |
| Quasi-oppositional differential evolution S Rahnamayan, HR Tizhoosh, MMA Salama 2007 IEEE congress on evolutionary computation, 2229-2236, 2007 | 490 | 2007 |
| A novel population initialization method for accelerating evolutionary algorithms S Rahnamayan, HR Tizhoosh, MMA Salama Computers & Mathematics with Applications 53 (10), 1605-1614, 2007 | 464 | 2007 |
| Opposition versus randomness in soft computing techniques S Rahnamayan, HR Tizhoosh, MMA Salama Applied Soft Computing 8 (2), 906-918, 2008 | 417 | 2008 |
| Image thresholding using type II fuzzy sets HR Tizhoosh Pattern recognition 38 (12), 2363-2372, 2005 | 380 | 2005 |
| Federated learning and differential privacy for medical image analysis M Adnan, S Kalra, JC Cresswell, GW Taylor, HR Tizhoosh Scientific reports 12 (1), 1953, 2022 | 332 | 2022 |
| Fuzzy image processing HR Tizhoosh Publisher: Springer-Verlag. Kartoniert (TB), Deutsch 10, 1997 | 275* | 1997 |
| Opposition-based differential evolution algorithms S Rahnamayan, HR Tizhoosh, MMA Salama 2006 IEEE international conference on evolutionary computation, 2010-2017, 2006 | 253 | 2006 |
| Opposition-based reinforcement learning HR Tizhoosh Journal of Advanced Computational Intelligence and Intelligent Informatics …, 2006 | 248 | 2006 |
| Fuzzy image processing: an overview HR Tizhoosh, H Haußecker Handbook on Computer Vision and Applications 2, 683-727, 1999 | 233* | 1999 |
| Convolutional neural networks for histopathology image classification: Training vs. using pre-trained networks B Kieffer, M Babaie, S Kalra, HR Tizhoosh 2017 seventh international conference on image processing theory, tools and …, 2017 | 203 | 2017 |
| Reinforcement learning based on actions and opposite actions HR Tizhoosh International conference on artificial intelligence and machine learning 414, 2005 | 170 | 2005 |
| Fine-tuning and training of densenet for histopathology image representation using tcga diagnostic slides A Riasatian, M Babaie, D Maleki, S Kalra, M Valipour, S Hemati, M Zaveri, ... Medical image analysis 70, 102032, 2021 | 169 | 2021 |
| Improving the convergence of backpropagation by opposite transfer functions M Ventresca, HR Tizhoosh The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006 | 158 | 2006 |
| Opposition-based differential evolution for optimization of noisy problems S Rahnamayan, HR Tizhoosh, MMA Salama 2006 IEEE International Conference on Evolutionary Computation, 1865-1872, 2006 | 151 | 2006 |
| A comparative study of CNN, BoVW and LBP for classification of histopathological images MD Kumar, M Babaie, S Zhu, S Kalra, HR Tizhoosh 2017 IEEE symposium series on computational intelligence (SSCI), 1-7, 2017 | 147 | 2017 |
| Yottixel–an image search engine for large archives of histopathology whole slide images S Kalra, HR Tizhoosh, C Choi, S Shah, P Diamandis, CJV Campbell, ... Medical Image Analysis 65, 101757, 2020 | 126 | 2020 |
| Representation learning of histopathology images using graph neural networks M Adnan, S Kalra, HR Tizhoosh Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 125 | 2020 |