Praveer Singh
Orcid: 0000-0001-6641-2030
According to our database1,
Praveer Singh
authored at least 31 papers
between 2014 and 2024.
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Bibliography
2024
Cycle-GANs Generated Difference Maps to Interpret Race Prediction from Medical Images.
Proceedings of the Ethics and Fairness in Medical Imaging, 2024
Addressing Catastrophic Forgetting by Modulating Global Batch Normalization Statistics for Medical Domain Expansion.
Proceedings of the Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, and Personalized Incremental Learning in Medicine, 2024
Conformal Prediction and Monte Carlo Inference for Addressing Uncertainty in Cervical Cancer Screening.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2024
2023
CoRR, 2023
A Deep Learning Based Framework for Joint Image Registration and Segmentation of Brain Metastases on Magnetic Resonance Imaging.
Proceedings of the Machine Learning for Healthcare Conference, 2023
2022
IEEE J. Biomed. Health Informatics, 2022
Estimating Test Performance for AI Medical Devices under Distribution Shift with Conformal Prediction.
CoRR, 2022
CoRR, 2022
Towards More Efficient Data Valuation in Healthcare Federated Learning Using Ensembling.
Proceedings of the Distributed, Collaborative, and Federated Learning, and Affordable AI and Healthcare for Resource Diverse Global Health, 2022
2021
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results.
CoRR, 2021
Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations.
CoRR, 2021
2020
IEEE Trans. Image Process., 2020
Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging.
npj Digit. Medicine, 2020
The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions.
CoRR, 2020
Assessing the (Un)Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging.
CoRR, 2020
Assessing the validity of saliency maps for abnormality localization in medical imaging.
CoRR, 2020
Proceedings of the Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning, 2020
Segmentation, Survival Prediction, and Uncertainty Estimation of Gliomas from Multimodal 3D MRI Using Selective Kernel Networks.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020
Diagnosability of Synthetic Retinal Fundus Images for Plus Disease Detection in Retinopathy of Prematurity.
Proceedings of the AMIA 2020, 2020
2019
Give me (un)certainty - An exploration of parameters that affect segmentation uncertainty.
CoRR, 2019
2018
Traitement d'images à haute résolution grâce à des techniques d'apprentissage en profondeur. (Processing high-resolution images through deep learning techniques).
PhD thesis, 2018
Improving Recognition of Complex Aerial Scenes Using a Deep Weakly Supervised Learning Paradigm.
IEEE Geosci. Remote. Sens. Lett., 2018
Int. J. Intell. Robotics Appl., 2018
Cloud-Gan: Cloud Removal for Sentinel-2 Imagery Using a Cyclic Consistent Generative Adversarial Networks.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
Effective Building Extraction by Learning to Detect and Correct Erroneous Labels in Segmentation Mask.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
2014
A Multilayer Markovian Model for Change Detection in Aerial Image Pairs with Large Time Differences.
Proceedings of the 22nd International Conference on Pattern Recognition, 2014