Viraj Kulkarni

Orcid: 0000-0001-8246-7234

According to our database1, Viraj Kulkarni authored at least 15 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of six.
  • Erdős number3 of five.

Timeline

Legend:

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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2023
A classical-quantum convolutional neural network for detecting pneumonia from chest radiographs.
Neural Comput. Appl., July, 2023

2022
Application of Federated Learning in Building a Robust COVID-19 Chest X-ray Classification Model.
CoRR, 2022

A deep learning approach for automated diagnosis of pulmonary embolism on computed tomographic pulmonary angiography.
BMC Medical Imaging, 2022

2021
Quantum computing methods for supervised learning.
Quantum Mach. Intell., 2021

Levels of Autonomous Radiology.
CoRR, 2021

Vulnerability Due to Training Order in Split Learning.
CoRR, 2021

Reducing Labelled Data Requirement for Pneumonia Segmentation using Image Augmentations.
CoRR, 2021

Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical Radiology Practice.
CoRR, 2021

Comparative Evaluation of 3D and 2D Deep Learning Techniques for Semantic Segmentation in CT Scans.
CoRR, 2021

Deep Learning Models for Calculation of Cardiothoracic Ratio from Chest Radiographs for Assisted Diagnosis of Cardiomegaly.
CoRR, 2021

Comparison of Privacy-Preserving Distributed Deep Learning Methods in Healthcare.
Proceedings of the Medical Image Understanding and Analysis - 25th Annual Conference, 2021

Automated Detection of COVID-19 from CT Scans using Convolutional Neural Networks.
Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods, 2021

2020
Role of Edge Device and Cloud Machine Learning in Point-of-Care Solutions Using Imaging Diagnostics for Population Screening.
CoRR, 2020

Automatic Grading of Knee Osteoarthritis on the Kellgren-Lawrence Scale from Radiographs Using Convolutional Neural Networks.
CoRR, 2020

Survey of Personalization Techniques for Federated Learning.
CoRR, 2020


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