Pseudo-labeling and confirmation bias in deep semi-supervised learning E Arazo, D Ortego, P Albert, NE O’Connor, K McGuinness 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 268 | 2020 |
Unsupervised label noise modeling and loss correction E Arazo, D Ortego, P Albert, N O’Connor, K McGuinness International Conference on Machine Learning, 312-321, 2019 | 262 | 2019 |
Towards robust learning with different label noise distributions D Ortego, E Arazo, P Albert, NE O'Connor, K McGuinness 2020 25th International Conference on Pattern Recognition (ICPR), 7020-7027, 2021 | 14 | 2021 |
Multi-Objective Interpolation Training for Robustness to Label Noise D Ortego, E Arazo, P Albert, NE O'Connor, K McGuinness Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 13 | 2021 |
Extracting Pasture Phenotype and Biomass Percentages using Weakly Supervised Multi-target Deep Learning on a Small Dataset B Narayanan, M Saadeldin, P Albert, K McGuinness, B Mac Namee arXiv preprint arXiv:2101.03198, 2021 | 6 | 2021 |
Relab: Reliable label bootstrapping for semi-supervised learning P Albert, D Ortego, E Arazo, N O'Connor, K McGuinness 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 5 | 2021 |
Semi-Supervised Dry Herbage Mass Estimation Using Automatic Data and Synthetic Images P Albert, M Saadeldin, B Narayanan, B Mac Namee, D Hennessy, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 2 | 2021 |
Using image analysis and machine learning to estimate sward clover content D Hennessy, M Saad, B Mac Namee, NE O'Connor, K McGuinness, ... Sensing–New Insights into Grassland Science and Practice, 132, 2021 | 1 | 2021 |
Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation P Albert, M Saadeldin, B Narayanan, B Mac Namee, D Hennessy, ... arXiv preprint arXiv:2204.09343, 2022 | | 2022 |
Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation P Albert, M Saadeldin, B Narayanan, B Mac Namee, D Hennessy, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | | 2022 |
Addressing out-of-distribution label noise in webly-labelled data P Albert, D Ortego, E Arazo, NE O'Connor, K McGuinness Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | | 2022 |
How Important is Importance Sampling for Deep Budgeted Training? E Arazo, D Ortego, P Albert, NE O'Connor, K McGuinness arXiv preprint arXiv:2110.14283, 2021 | | 2021 |
Unsupervised label noise modeling and loss correction E Arazo Sánchez, D Ortego, P Albert, NE O'Connor, K McGuinness MIR Press, 2019 | | 2019 |
Supplementary material for Addressing out-of-distribution label noise in webly-labelled data P Albert, D Ortego, E Arazo, NE O’Connor, K McGuinness | | |