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ORCIDEric Arazo Sanchez
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2020 – today
- 2024
[c21]Sidra Aleem, Fangyijie Wang, Mayug Maniparambil, Eric Arazo, Julia Dietlmeier, Kathleen M. Curran, Noel E. O'Connor, Suzanne Little:
Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero-shot Medical Image Segmentation. CVPR Workshops 2024: 5184-5193- [c20]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 - [c19]Sidra Aleem, Julia Dietlmeier, Eric Arazo, Suzanne Little:
ConvLoRA and AdaBN Based Domain Adaptation via Self-Training. ISBI 2024: 1-5 - [c18]Carles García-Cabrera
, Eric Arazo Sanchez, Enric Moreu, Kathleen M. Curran, Noel E. O'Connor, Kevin McGuinness:
Synthetic Balancing of Cardiac MRI Datasets. MIUA (2) 2024: 353-365 - [c17]Eric Arazo, Hristo Stoev, Cristian Bosch, Andrés L. Suárez-Cetrulo, Ricardo Simon Carbajo:
Xpression: A Unifying Metric to Optimize Compression and Explainability Robustness of AI Models. xAI (1) 2024: 370-382 - [i17]Sidra Aleem, Julia Dietlmeier, Eric Arazo, Suzanne Little:
ConvLoRA and AdaBN based Domain Adaptation via Self-Training. CoRR abs/2402.04964 (2024) - [i16]Sidra Aleem, Fangyijie Wang, Mayug Maniparambil, Eric Arazo, Julia Dietlmeier, Guénolé Silvestre, Kathleen M. Curran, Noel E. O'Connor, Suzanne Little:
Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero shot Medical Image Segmentation. CoRR abs/2404.06362 (2024) - [i15]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
- [j1]Enric Moreu, Eric Arazo, Kevin McGuinness, Noel E. O'Connor:
Joint one-sided synthetic unpaired image translation and segmentation for colorectal cancer prevention. Expert Syst. J. Knowl. Eng. 40(6) (2023) - [c16]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 - [c15]Enric Moreu, Eric Arazo, Kevin McGuinness, Noel E. O'Connor:
Self-Supervised and Semi-Supervised Polyp Segmentation using Synthetic Data. IJCNN 2023: 1-9 - [c14]Sen Yan, Shaoshu Zhu, Jaime B. Fernandez, Eric Arazo Sanchez, Yingqi Gu, Noel E. O'Connor, David O'Connor, Mingming Liu:
Breathing Green: Maximising Health and Environmental Benefits for Active Transportation Users Leveraging Large Scale Air Quality Data. ITSC 2023: 5496-5503 - [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 - [i14]Enric Moreu, Eric Arazo, Kevin McGuinness, Noel E. O'Connor:
Joint one-sided synthetic unpaired image translation and segmentation for colorectal cancer prevention. CoRR abs/2307.11253 (2023) - [i13]Enric Moreu, Eric Arazo, Kevin McGuinness, Noel E. O'Connor:
Self-Supervised and Semi-Supervised Polyp Segmentation using Synthetic Data. CoRR abs/2307.12033 (2023) - 2022
- [c12]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 - [c11]Carles García-Cabrera, Eric Arazo, Kathleen M. Curran, Noel E. O'Connor, Kevin McGuinness:
Cardiac Segmentation Using Transfer Learning Under Respiratory Motion Artifacts. STACOM@MICCAI 2022: 392-398 - [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 - [i12]Eric Arazo, Robin Aly, Kevin McGuinness:
Segmentation Enhanced Lameness Detection in Dairy Cows from RGB and Depth Video. CoRR abs/2206.04449 (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]Carles García-Cabrera, Eric Arazo, Kathleen M. Curran, Noel E. O'Connor, Kevin McGuinness:
Cardiac Segmentation using Transfer Learning under Respiratory Motion Artifacts. CoRR abs/2209.09714 (2022) - [i9]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]Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
How Important is Importance Sampling for Deep Budgeted Training? BMVC 2021: 335 - [c8]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 - [c7]Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness:
ReLaB: Reliable Label Bootstrapping for Semi-Supervised Learning. IJCNN 2021: 1-8 - [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]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
- [c6]Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
Towards Robust Learning with Different Label Noise Distributions. ICPR 2020: 7020-7027 - [c5]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 - [i6]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) - [i5]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
- [c4]Diego Ortego, Kevin McGuinness, Juan C. SanMiguel, Eric Arazo, José M. Martínez, Noel E. O'Connor:
On guiding video object segmentation. CBMI 2019: 1-6 - [c3]Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness:
Unsupervised Label Noise Modeling and Loss Correction. ICML 2019: 312-321 - [c2]Alan F. Smeaton, Yvette Graham, Kevin McGuinness, Noel E. O'Connor, Seán Quinn, Eric Arazo Sanchez:
Exploring the Impact of Training Data Bias on Automatic Generation of Video Captions. MMM (1) 2019: 178-190 - [i4]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) - [i3]Diego Ortego, Kevin McGuinness, Juan C. SanMiguel, Eric Arazo, José M. Martínez, Noel E. O'Connor:
On guiding video object segmentation. CoRR abs/1904.11256 (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) - 2017
- [c1]Haithem Afli, Feiyan Hu, Jinhua Du, Daniel Cosgrove, Kevin McGuinness, Noel E. O'Connor, Eric Arazo Sanchez, Jiang Zhou, Alan F. Smeaton:
Dublin City University Participation in the VTT Track at TRECVid 2017. TRECVID 2017
Coauthor Index
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