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), 2019 | 866 | 2019 |
Unsupervised label noise modeling and loss correction E Arazo, D Ortego, P Albert, NE O'Connor, K McGuinness International Conference on Machine Learning (ICML), 2019 | 645 | 2019 |
Shallow and deep convolutional networks for saliency prediction J Pan, E Sayrol, X Giro-i-Nieto, K McGuinness, NE O'Connor Computer Vision and Pattern Recognition (CVPR), 598-606, 2016 | 564 | 2016 |
SalGAN: Visual saliency prediction with generative adversarial networks J Pan, C Canton, K McGuinness, NE O’Connor, J Torres, E Sayrol, ... CVPR 2017 Scene Understanding Workshop (SUNw), 2017 | 500 | 2017 |
A comparative evaluation of interactive segmentation algorithms K McGuinness, NE O’connor Pattern Recognition 43 (2), 434-444, 2010 | 382 | 2010 |
Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks J Antony, K McGuinness, NE O'Connor, K Moran 2016 23rd international conference on pattern recognition (ICPR), 1195-1200, 2016 | 303 | 2016 |
Bags of local convolutional features for scalable instance search E Mohedano, K McGuinness, NE O'Connor, A Salvador, F Marques, ... International Conference on Multimedia Retrieval (ICMR), 327-331, 2016 | 198 | 2016 |
Fully convolutional crowd counting on highly congested scenes M Marsden, K McGuinness, S Little, NE O'Connor International Joint Conference on Computer Vision, Imaging and Computer …, 2016 | 192 | 2016 |
Automatic detection of knee joints and quantification of knee osteoarthritis severity using convolutional neural networks J Antony, K McGuinness, K Moran, NE O’Connor Machine Learning and Data Mining in Pattern Recognition: 13th International …, 2017 | 179 | 2017 |
ResnetCrowd: A residual deep learning architecture for crowd counting, violent behaviour detection and crowd density level classification M Marsden, K McGuinness, S Little, NE O'Connor IEEE International Conference on Advanced Video and Signal Based …, 2017 | 155 | 2017 |
Saltinet: Scan-path prediction on 360 degree images using saliency volumes M Assens Reina, X Giro-i-Nieto, K McGuinness, NE O'Connor International Conference on Computer Vision (ICCV) Workshops, 2331-2338, 2017 | 130 | 2017 |
Multi-Objective Interpolation Training for Robustness to Label Noise D Ortego, E Arazo, P Albert, NE O'Connor, K McGuinness Computer Vision and Pattern Recognition (CVPR), 2021 | 107 | 2021 |
People, penguins and petri dishes: Adapting object counting models to new visual domains and object types without forgetting M Marsden, K McGuinness, S Little, CE Keogh, NE O'Connor Computer Vision and Pattern Recognition (CVPR), 8070-8079, 2018 | 102 | 2018 |
WAV2PIX: Speech-conditioned Face Generation using Generative Adversarial Networks. AC Duarte, F Roldan, M Tubau, J Escur, S Pascual, A Salvador, ... ICASSP 2019, 8633-8637, 2019 | 93 | 2019 |
Simple vs complex recurrences for video saliency prediction P Linardos, E Mohedano, JJ Nieto, NE O'Connor, X Giro-i-Nieto, ... British Machine Vision Conference (BMVC), 2019 | 90* | 2019 |
PathGAN: visual scanpath prediction with generative adversarial networks M Assens, X Giro-i-Nieto, K McGuinness, NE O'Connor Proceedings of the European Conference on Computer Vision (ECCV), 2018 | 84 | 2018 |
Holistic features for real-time crowd behaviour anomaly detection M Marsden, K McGuinness, S Little, NE O'Connor 2016 IEEE International Conference on Image Processing (ICIP), 918-922, 2016 | 80 | 2016 |
Unsupervised Contrastive Learning of Sound Event Representations E Fonseca, D Ortego, K McGuinness, NE O'Connor, X Serra IEEE International Conference on Acoustics, Speech and Signal Processing …, 2021 | 70 | 2021 |
Predicting knee osteoarthritis severity: comparative modeling based on patient’s data and plain X-ray images J Abedin, J Antony, K McGuinness, K Moran, NE O’Connor, ... Scientific reports 9 (1), 5761, 2019 | 68 | 2019 |
Toward automated evaluation of interactive segmentation K McGuinness, NE O’Connor Computer Vision and Image Understanding 115 (6), 868-884, 2011 | 63 | 2011 |