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ORCIDPaul Albert
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2020 – today
- 2024
[c16]Muhammad Zawish, Paul Albert, Flavio Esposito, Steven Davy, Lizy Abraham:
Energy-Efficient Uncertainty-Aware Biomass Composition Prediction at the Edge. CVPR Workshops 2024: 5357-5365- [c15]Paul Albert, Jack Valmadre, Eric Arazo, Tarun Krishna, Noel E. O'Connor, Kevin McGuinness:
An Accurate Detection Is Not All You Need to Combat Label Noise in Web-Noisy Datasets. ECCV (49) 2024: 55-72 - [i16]Muhammad Zawish, Paul Albert
, Flavio Esposito, Steven Davy, Lizy Abraham:
Energy-Efficient Uncertainty-Aware Biomass Composition Prediction at the Edge. CoRR abs/2404.11230 (2024) - [i15]Frederic Z. Zhang, Paul Albert, Cristian Rodriguez Opazo, Anton van den Hengel, Ehsan Abbasnejad:
Knowledge Composition using Task Vectors with Learned Anisotropic Scaling. CoRR abs/2407.02880 (2024) - [i14]Paul Albert, Jack Valmadre, Eric Arazo, Tarun Krishna, Noel E. O'Connor, Kevin McGuinness:
An accurate detection is not all you need to combat label noise in web-noisy datasets. CoRR abs/2407.05528 (2024) - 2023
- [c14]Tarun Krishna, Ayush K. Rai, Alexandru Drimbarean, Eric Arazo, Paul Albert, Alan F. Smeaton, Kevin McGuinness, Noel E. O'Connor:
Unifying Synergies between Self-supervised Learning and Dynamic Computation. BMVC 2023: 394-401 - [c13]Paul Albert, Eric Arazo, Tarun Krishna, Noel E. O'Connor, Kevin McGuinness:
Is your noise correction noisy? PLS: Robustness to label noise with two stage detection. WACV 2023: 118-127 - 2022
- [c12]Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Noel E. O'Connor, Kevin McGuinness:
Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation. CVPR Workshops 2022: 1635-1645 - [c11]Paul Albert, Eric Arazo, Noel E. O'Connor, Kevin McGuinness:
Embedding Contrastive Unsupervised Features to Cluster In- And Out-of-Distribution Noise in Corrupted Image Datasets. ECCV (31) 2022: 402-419 - [c10]Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness:
Addressing out-of-distribution label noise in webly-labelled data. WACV 2022: 2393-2402 - [i13]Paul Albert, Mohamed Saadeldin, Badri Narayanan, Jaime B. Fernandez, Brian Mac Namee, Deirdre Hennessy, Noel E. O'Connor, Kevin McGuinness:
Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation. CoRR abs/2204.08271 (2022) - [i12]Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling H. O'Connor, Noel E. O'Connor, Kevin McGuinness:
Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation. CoRR abs/2204.09343 (2022) - [i11]Paul Albert, Eric Arazo, Noel E. O'Connor, Kevin McGuinness:
Embedding contrastive unsupervised features to cluster in- and out-of-distribution noise in corrupted image datasets. CoRR abs/2207.01573 (2022) - [i10]Paul Albert, Eric Arazo, Tarun Krishna, Noel E. O'Connor, Kevin McGuinness:
Is your noise correction noisy? PLS: Robustness to label noise with two stage detection. CoRR abs/2210.04578 (2022) - 2021
- [c9]Badri Narayanan, Mohamed Saadeldin, Paul Albert, Kevin McGuinness, Noel E. O'Connor, Brian Mac Namee:
Adaptation of Compositional Data Analysis in Deep Learning to Predict Pasture Biomass Proportions. AICS 2021: 176-187 - [c8]Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
How Important is Importance Sampling for Deep Budgeted Training? BMVC 2021: 335 - [c7]Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
Multi-Objective Interpolation Training for Robustness To Label Noise. CVPR 2021: 6606-6615 - [c6]Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling O'Connor, Noel E. O'Connor, Kevin McGuinness:
Semi-supervised dry herbage mass estimation using automatic data and synthetic images. ICCVW 2021: 1284-1293 - [c5]Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness:
ReLaB: Reliable Label Bootstrapping for Semi-Supervised Learning. IJCNN 2021: 1-8 - [i9]Badri Narayanan, Mohamed Saadeldin, Paul Albert, Kevin McGuinness, Brian Mac Namee:
Extracting Pasture Phenotype and Biomass Percentages using Weakly Supervised Multi-target Deep Learning on a Small Dataset. CoRR abs/2101.03198 (2021) - [i8]Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness:
Addressing out-of-distribution label noise in webly-labelled data. CoRR abs/2110.13699 (2021) - [i7]Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling O'Connor, Noel E. O'Connor, Kevin McGuinness:
Semi-supervised dry herbage mass estimation using automatic data and synthetic images. CoRR abs/2110.13719 (2021) - [i6]Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
How Important is Importance Sampling for Deep Budgeted Training? CoRR abs/2110.14283 (2021) - 2020
- [c4]Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
Towards Robust Learning with Different Label Noise Distributions. ICPR 2020: 7020-7027 - [c3]Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning. IJCNN 2020: 1-8 - [i5]Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness:
ReLaB: Reliable Label Bootstrapping for Semi-Supervised Learning. CoRR abs/2007.11866 (2020) - [i4]Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
Multi-Objective Interpolation Training for Robustness to Label Noise. CoRR abs/2012.04462 (2020)
2010 – 2019
- 2019
- [c2]Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
Unsupervised Label Noise Modeling and Loss Correction. ICML 2019: 312-321 - [i3]Eric Arazo Sanchez, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
Unsupervised label noise modeling and loss correction. CoRR abs/1904.11238 (2019) - [i2]Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning. CoRR abs/1908.02983 (2019) - [i1]Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
Towards Robust Learning with Different Label Noise Distributions. CoRR abs/1912.08741 (2019) - 2012
- [c1]Paul Albert, Kristi L. Holmes, Katy Börner, Mike Conlon:
Research discovery through linked open data. JCDL 2012: 429-430
1990 – 1999
- 1999
- [j1]Geoffry S. Howard, Thomas Bodnovich, Thomas Janicki, Jens Liegle, Steven Klein, Paul Albert, David Cannon:
The efficacy of matching information systems development methodologies with application characteristics - an empirical study. J. Syst. Softw. 45(3): 177-195 (1999)
Coauthor Index
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last updated on 2024-11-15 20:40 CET by the dblp team
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