Eric Arazo Sanchez

Orcid: 0000-0001-9769-3592

According to our database¹, Eric Arazo Sanchez authored at least 19 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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On csauthors.net:

Bibliography

2024

ConvLoRA and AdaBN based Domain Adaptation via Self-Training.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Joint one-sided synthetic unpaired image translation and segmentation for colorectal cancer prevention.

[BibT_eX]

[DOI]

Expert Syst. J. Knowl. Eng., July, 2023

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

[BibT_eX]

[DOI]

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

Breathing Green: Maximising Health and Environmental Benefits for Active Transportation Users Leveraging Large Scale Air Quality Data.

[BibT_eX]

[DOI]

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

Self-Supervised and Semi-Supervised Polyp Segmentation using Synthetic Data.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2023

Unifying Synergies between Self-supervised Learning and Dynamic Computation.

[BibT_eX]

[DOI]

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

2022

Segmentation Enhanced Lameness Detection in Dairy Cows from RGB and Depth Video.

[BibT_eX]

[DOI]

Eric Arazo

Robin Aly

Kevin McGuinness

CoRR, 2022

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

[BibT_eX]

[DOI]

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

Cardiac Segmentation Using Transfer Learning Under Respiratory Motion Artifacts.

[BibT_eX]

[DOI]

Carles García-Cabrera

Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers, 2022

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

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

ReLaB: Reliable Label Bootstrapping for Semi-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2021

Multi-Objective Interpolation Training for Robustness To Label Noise.

[BibT_eX]

[DOI]

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

How Important is Importance Sampling for Deep Budgeted Training?

[BibT_eX]

[DOI]

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

2020

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

[BibT_eX]

[DOI]

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

Towards Robust Learning with Different Label Noise Distributions.

[BibT_eX]

[DOI]

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

2019

Exploring the Impact of Training Data Bias on Automatic Generation of Video Captions.

[BibT_eX]

[DOI]

Proceedings of the MultiMedia Modeling - 25th International Conference, 2019

Unsupervised Label Noise Modeling and Loss Correction.

[BibT_eX]

[DOI]

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

On guiding video object segmentation.

[BibT_eX]

[DOI]

Proceedings of the 2019 International Conference on Content-Based Multimedia Indexing, 2019

2017

Dublin City University Participation in the VTT Track at TRECVid 2017.

[BibT_eX]

[DOI]

Proceedings of the 2017 TREC Video Retrieval Evaluation, 2017

Eric Arazo Sanchez

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