Sarah M. Hooper

Orcid: 0000-0001-9366-2174

According to our database1, Sarah M. Hooper authored at least 12 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2025
SNRAware: Improved Deep Learning MRI Denoising with SNR Unit Training and G-factor Map Augmentation.
CoRR, March, 2025

A Study on Context Length and Efficient Transformers for Biomedical Image Analysis.
CoRR, January, 2025

2024
A Study on Context Length and Efficient Transformers for Biomedical Image Analysis.
Proceedings of the Machine Learning for Health, 2024

2023
A case for reframing automated medical image classification as segmentation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity.
Proceedings of the Machine Learning for Healthcare Conference, 2022

Multi-tracer PET Imaging Using Deep Learning: Applications in Patients with High-Grade Gliomas.
Proceedings of the Predictive Intelligence in Medicine - 5th International Workshop, 2022

2021
Superiorized Photo-Acoustic Non-NEgative Reconstruction (SPANNER) for Clinical Photoacoustic Imaging.
IEEE Trans. Medical Imaging, 2021

Observational Supervision for Medical Image Classification Using Gaze Data.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Cut out the annotator, keep the cutout: better segmentation with weak supervision.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Assessing Robustness to Noise: Low-Cost Head CT Triage.
CoRR, 2020

Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods.
Proceedings of the 37th International Conference on Machine Learning, 2020


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