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Kevin McGuinness
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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
4852016
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
4002017
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
3642019
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
3582019
A comparative evaluation of interactive segmentation algorithms
K McGuinness, NE O’connor
Pattern Recognition 43 (2), 434-444, 2010
3232010
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
2142016
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
1802016
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
1682016
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
1282017
Automatic detection of knee joints and quantification of knee osteoarthritis severity using convolutional neural networks
J Antony, K McGuinness, K Moran, NE O’Connor
International conference on machine learning and data mining in pattern …, 2017
1192017
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
872017
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
762018
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
732016
WAV2PIX: Speech-conditioned Face Generation using Generative Adversarial Networks.
AC Duarte, F Roldan, M Tubau, J Escur, S Pascual, A Salvador, ...
ICASSP, 8633-8637, 2019
632019
Toward automated evaluation of interactive segmentation
K McGuinness, NE O’Connor
Computer Vision and Image Understanding 115 (6), 868-884, 2011
592011
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
56*2019
The video browser showdown: a live evaluation of interactive video search tools
K Schoeffmann, D Ahlström, W Bailer, C Cobârzan, F Hopfgartner, ...
International Journal of Multimedia Information Retrieval 3 (2), 113-127, 2014
502014
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
482018
SalGAN: Visual saliency prediction with adversarial networks
J Pan, E Sayrol, XG Nieto, CC Ferrer, J Torres, K McGuinness, ...
CVPR Scene Understanding Workshop (SUNw), 2017
442017
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), 1-11, 2019
432019
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