Eric Arazo

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 30

Top Topics

Colorectal Cancer

Image Segmentation

Top Venues

Publications

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 (2024)
Sidra Aleem, Julia Dietlmeier, Eric Arazo, Suzanne Little
ConvLoRA and AdaBN based Domain Adaptation via Self-Training. CoRR (2024)
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 (2024)
Enric Moreu, Eric Arazo, Kevin McGuinness, Noel E. O'Connor
Self-Supervised and Semi-Supervised Polyp Segmentation using Synthetic Data. IJCNN (2023)
Enric Moreu, Eric Arazo, Kevin McGuinness, Noel E. O'Connor
Self-Supervised and Semi-Supervised Polyp Segmentation using Synthetic Data. CoRR (2023)
Enric Moreu, Eric Arazo, Kevin McGuinness, Noel E. O'Connor
Joint one-sided synthetic unpaired image translation and segmentation for colorectal cancer prevention. CoRR (2023)
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)
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)
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)
Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness
Addressing out-of-distribution label noise in webly-labelled data. WACV (2022)
Carles García-Cabrera, Eric Arazo, Kathleen M. Curran, Noel E. O'Connor, Kevin McGuinness
Cardiac Segmentation using Transfer Learning under Respiratory Motion Artifacts. CoRR (2022)
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)
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 (2022)
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)
Eric Arazo, Robin Aly, Kevin McGuinness
Segmentation Enhanced Lameness Detection in Dairy Cows from RGB and Depth Video. CoRR (2022)
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 (2022)
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
How Important is Importance Sampling for Deep Budgeted Training? CoRR (2021)
Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness
Multi-Objective Interpolation Training for Robustness To Label Noise. CVPR (2021)
Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness
ReLaB: Reliable Label Bootstrapping for Semi-Supervised Learning. IJCNN (2021)
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
How Important is Importance Sampling for Deep Budgeted Training? BMVC (2021)
Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness
Addressing out-of-distribution label noise in webly-labelled data. CoRR (2021)
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning. IJCNN (2020)
Paul Albert, Diego Ortego, Eric Arazo, Noel E. O'Connor, Kevin McGuinness
ReLaB: Reliable Label Bootstrapping for Semi-Supervised Learning. CoRR (2020)
Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness
Towards Robust Learning with Different Label Noise Distributions. ICPR (2020)
Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness
Multi-Objective Interpolation Training for Robustness to Label Noise. CoRR (2020)
Diego Ortego, Kevin McGuinness, Juan C. SanMiguel, Eric Arazo, José M. Martínez, Noel E. O'Connor
On guiding video object segmentation. CoRR (2019)
Diego Ortego, Eric Arazo, Paul Albert, Noel E. O'Connor, Kevin McGuinness
Towards Robust Learning with Different Label Noise Distributions. CoRR (2019)
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
Unsupervised Label Noise Modeling and Loss Correction. ICML (2019)
Eric Arazo, Diego Ortego, Paul Albert, Noel E. O'Connor, Kevin McGuinness
Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning. CoRR (2019)
Diego Ortego, Kevin McGuinness, Juan C. SanMiguel, Eric Arazo, José M. Martínez, Noel E. O'Connor
On guiding video object segmentation. CBMI (2019)