| Incorporating privileged information through metric learning S Fouad, P Tino, S Raychaudhury, P Schneider IEEE transactions on neural networks and learning systems 24 (7), 1086-1098, 2013 | 86 | 2013 |
| Automatic thresholding from the gradients of region boundaries G Landini, DA Randell, S Fouad, A Galton Journal of microscopy 265 (2), 185-195, 2017 | 46 | 2017 |
| Adaptive metric learning vector quantization for ordinal classification S Fouad, P Tino Neural computation 24 (11), 2825-2851, 2012 | 28 | 2012 |
| Unsupervised morphological segmentation of tissue compartments in histopathological images S Fouad, D Randell, A Galton, H Mehanna, G Landini PloS one 12 (11), e0188717, 2017 | 27 | 2017 |
| Learning using privileged information in prototype based models S Fouad, P Tino, S Raychaudhury, P Schneider Artificial Neural Networks and Machine Learning–ICANN 2012: 22nd …, 2012 | 18 | 2012 |
| Mereotopological correction of segmentation errors in histological imaging DA Randell, A Galton, S Fouad, H Mehanna, G Landini Journal of Imaging 3 (4), 63, 2017 | 17 | 2017 |
| Classifying cognitive profiles using machine learning with privileged information in mild cognitive impairment HH Alahmadi, Y Shen, S Fouad, CDB Luft, P Bentham, Z Kourtzi, P Tino Frontiers in Computational Neuroscience, 117, 2016 | 17 | 2016 |
| Ordinal-based metric learning for learning using privileged information S Fouad, P Tiňo The 2013 International Joint Conference on Neural Networks (IJCNN), 1-8, 2013 | 16 | 2013 |
| Novel applications of discrete mereotopology to mathematical morphology G Landini, A Galton, D Randell, S Fouad Signal Processing: Image Communication 76, 109-117, 2019 | 14 | 2019 |
| Unsupervised superpixel-based segmentation of histopathological images with consensus clustering S Fouad, D Randell, A Galton, H Mehanna, G Landini Medical Image Understanding and Analysis: 21st Annual Conference, MIUA 2017 …, 2017 | 14 | 2017 |
| Ontological Levels in Histological Imaging A Galton, G Landini, D Randell, S Fouad Artificial Intelligence and Digital Microscopy, 4, 2018 | 10 | 2018 |
| Epithelium and stroma identification in histopathological images using unsupervised and semi-supervised superpixel-based segmentation S Fouad, D Randell, A Galton, H Mehanna, G Landini Journal of Imaging 3 (4), 61, 2017 | 10 | 2017 |
| Ontological Levels in Histological Imaging. A Galton, G Landini, DA Randell, S Fouad FOIS, 271-284, 2016 | 10 | 2016 |
| Discrete mereotopology in histological imaging G Landini, DA Randell, AP Galton Proceedings of the 17th conference on Medical Image Understanding and …, 2013 | 9 | 2013 |
| Morphological separation of clustered nuclei in histological images S Fouad, G Landini, D Randell, A Galton Image Analysis and Recognition: 13th International Conference, ICIAR 2016 …, 2016 | 7 | 2016 |
| A Framework of New Hybrid Features for Intelligent Detection of Zero Hour Phishing Websites. SH Nagunwa T., Naqvi S., Fouad S. International Joint Conference: 12th International Conference on …, 2019 | 6* | 2019 |
| Metric learning for incorporating privileged information in prototype-based models S Fouad University of Birmingham, 2013 | 4 | 2013 |
| Transfer learning approach for detecting psychological distress in brexit tweets SK Palicki, S Fouad, M Adedoyin-Olowe, ZS Abdallah Proceedings of the 36th Annual ACM Symposium on Applied Computing, 967-975, 2021 | 3 | 2021 |
| Human papilloma virus detection in oropharyngeal carcinomas with in situ hybridisation using hand crafted morphological features and deep central attention residual networks S Fouad, G Landini, M Robinson, TH Song, H Mehanna Computerized Medical Imaging and Graphics 88, 101853, 2021 | 3 | 2021 |
| Epithelial segmentation from in situ hybridisation histological samples using a deep central attention learning approach TH Song, G Landini, S Fouad, H Mehanna IEEE International Symposium on Biomedical Imaging (ISBI 2019) . Institute …, 2019 | 3 | 2019 |
Gabriel LandiniUniversity of Birmingham, U.K.Verified email at bham.ac.uk
