Praveer Singh

Orcid: 0000-0001-6641-2030

According to our database1, Praveer Singh authored at least 27 papers between 2014 and 2023.

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

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
A generalized framework to predict continuous scores from medical ordinal labels.
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
SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging.
IEEE J. Biomed. Health Informatics, 2022

Estimating Test Performance for AI Medical Devices under Distribution Shift with Conformal Prediction.
CoRR, 2022

Three Applications of Conformal Prediction for Rating Breast Density in Mammography.
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.
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CoRR, 2021

Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations.
CoRR, 2021

Deploying clinical machine learning? Consider the following...
CoRR, 2021

Addressing catastrophic forgetting for medical domain expansion.
CoRR, 2021

2020
Deep Tone Mapping Operator for High Dynamic Range Images.
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

Towards Trainable Saliency Maps in Medical Imaging.
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


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

Autonomous robotic system for tunnel structural inspection and assessment.
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

Unsupervised Representation Learning by Predicting Image Rotations.
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


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