Pranav Kulkarni
Orcid: 0000-0001-5544-5515
According to our database1,
Pranav Kulkarni
authored at least 36 papers
between 2018 and 2024.
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Bibliography
2024
Weight-Constrained Sparse Arrays For Direction of Arrival Estimation Under High Mutual Coupling.
IEEE Trans. Signal Process., 2024
Improving Multi-Center Generalizability of GAN-Based Fat Suppression using Federated Learning.
CoRR, 2024
Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations.
CoRR, 2024
Hidden in Plain Sight: Undetectable Adversarial Bias Attacks on Vulnerable Patient Populations.
CoRR, 2024
Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification.
Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024
Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024
Proceedings of the IEEE International Conference on Acoustics, 2024
Privacy-Preserving Collaboration for Multi-Organ Segmentation via Federated Learning from Sites with Partial Labels.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Proceedings of the Designing Interactive Systems Conference, 2024
2023
Periodicity-Aware Signal Denoising Using Capon-Optimized Ramanujan Filter Banks and Pruned Ramanujan Dictionaries.
IEEE Trans. Signal Process., 2023
One Copy Is All You Need: Resource-Efficient Streaming of Medical Imaging Data at Scale.
CoRR, 2023
High-Throughput AI Inference for Medical Image Classification and Segmentation using Intelligent Streaming.
CoRR, 2023
Text2Cohort: Democratizing the NCI Imaging Data Commons with Natural Language Cohort Discovery.
CoRR, 2023
Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels.
CoRR, 2023
SegViz: A Federated Learning Framework for Medical Image Segmentation from Distributed Datasets with Different and Incomplete Annotations.
CoRR, 2023
Surgical Aggregation: A Federated Learning Framework for Harmonizing Distributed Datasets with Diverse Tasks.
CoRR, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
Exploring the digital support needs of caregivers of people with serious mental illness.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023
2022
Sensors, 2022
From Competition to Collaboration: Making Toy Datasets on Kaggle Clinically Useful for Chest X-Ray Diagnosis Using Federated Learning.
CoRR, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
Proceedings of the CHI '22: CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April 2022, 2022
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022
2021
Periodic Signal Denoising: An Analysis-Synthesis Framework Based on Ramanujan Filter Banks and Dictionaries.
Proceedings of the IEEE International Conference on Acoustics, 2021
Feature Engineering for DOA Estimation using a Convolutional Neural Network, for Sparse Arrays.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021
2020
Circuits Syst. Signal Process., 2020
Circuits Syst. Signal Process., 2020
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020
2019
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019
2018
Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB).
BMC Bioinform., 2018