Paul Albert

According to our database, Paul Albert authored at least 21 papers between 1999 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Knowledge Composition using Task Vectors with Learned Anisotropic Scaling.

Frederic Z. Zhang, Paul Albert, Cristian Rodriguez Opazo, Anton van den Hengel, Ehsan Abbasnejad

CoRR, 2024

An Accurate Detection Is Not All You Need to Combat Label Noise in Web-Noisy Datasets.

Paul Albert, Jack Valmadre, Eric Arazo, Tarun Krishna, Noel E. O'Connor, Kevin McGuinness

Proceedings of the Computer Vision - ECCV 2024, 2024

Energy-Efficient Uncertainty-Aware Biomass Composition Prediction at the Edge.

Muhammad Zawish, Paul Albert, Flavio Esposito, Steven Davy, Lizy Abraham

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Is your noise correction noisy? PLS: Robustness to label noise with two stage detection.

Paul Albert, Eric Arazo, Tarun Krishna, Noel E. O'Connor, Kevin McGuinness

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Unifying Synergies between Self-supervised Learning and Dynamic Computation.

Tarun Krishna, Ayush K. Rai, Alexandru Drimbarean, Eric Arazo, Paul Albert, Alan F. Smeaton, Kevin McGuinness, Noel E. O'Connor

Proceedings of the 34th British Machine Vision Conference 2023, 2023

2022

Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation.

Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling H. O'Connor, Noel E. O'Connor, Kevin McGuinness

CoRR, 2022

Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation.

Paul Albert, Mohamed Saadeldin, Badri Narayanan, Jaime B. Fernandez, Brian Mac Namee, Deirdre Hennessy, Noel E. O'Connor, Kevin McGuinness

CoRR, 2022

Addressing out-of-distribution label noise in webly-labelled data.

Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Embedding Contrastive Unsupervised Features to Cluster In- And Out-of-Distribution Noise in Corrupted Image Datasets.

Paul Albert, Eric Arazo, Noel E. O'Connor, Kevin McGuinness

Proceedings of the Computer Vision - ECCV 2022, 2022

Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation.

Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Noel E. O'Connor, Kevin McGuinness

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Extracting Pasture Phenotype and Biomass Percentages using Weakly Supervised Multi-target Deep Learning on a Small Dataset.

Badri Narayanan, Mohamed Saadeldin, Paul Albert, Kevin McGuinness, Brian Mac Namee

CoRR, 2021

ReLaB: Reliable Label Bootstrapping for Semi-Supervised Learning.

Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness

Proceedings of the International Joint Conference on Neural Networks, 2021

Semi-supervised dry herbage mass estimation using automatic data and synthetic images.

Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling O'Connor, Noel E. O'Connor, Kevin McGuinness

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Multi-Objective Interpolation Training for Robustness To Label Noise.

Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

How Important is Importance Sampling for Deep Budgeted Training?

Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Adaptation of Compositional Data Analysis in Deep Learning to Predict Pasture Biomass Proportions.

Badri Narayanan, Mohamed Saadeldin, Paul Albert, Kevin McGuinness, Noel E. O'Connor, Brian Mac Namee

Proceedings of the 29th Irish Conference on Artificial Intelligence and Cognitive Science 2021, 2021

2020

Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning.

Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Towards Robust Learning with Different Label Noise Distributions.

Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness

Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019

Unsupervised Label Noise Modeling and Loss Correction.

Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness

Proceedings of the 36th International Conference on Machine Learning, 2019

2012

Research discovery through linked open data.

Paul Albert, Kristi L. Holmes, Katy Börner, Mike Conlon

Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries, 2012

1999

The efficacy of matching information systems development methodologies with application characteristics - an empirical study.

Geoffry S. Howard, Thomas Bodnovich, Thomas Janicki, Jens Liegle, Steven Klein, Paul Albert, David Cannon

J. Syst. Softw., 1999