Bharath Srinivas Prabakaran

Orcid: 0000-0003-0557-2166

According to our database1, Bharath Srinivas Prabakaran authored at least 23 papers between 2017 and 2023.

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

Timeline

Legend:

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PhD thesis 
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On csauthors.net:

Bibliography

2023
Exploring Weakly Supervised Semantic Segmentation Ensembles for Medical Imaging Systems.
CoRR, 2023

Image Label based Semantic Segmentation Framework using Object Perimeters.
CoRR, 2023

BoundaryCAM: A Boundary-based Refinement Framework for Weakly Supervised Semantic Segmentation of Medical Images.
CoRR, 2023

autoXFPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems.
CoRR, 2023

UnbiasedNets: A Dataset Diversification Framework for Robustness Bias Alleviation in Neural Networks.
CoRR, 2023

FPUS23: An Ultrasound Fetus Phantom Dataset With Deep Neural Network Evaluations for Fetus Orientations, Fetal Planes, and Anatomical Features.
IEEE Access, 2023

ReFit: A Framework for Refinement of Weakly Supervised Semantic Segmentation Using Object Border Fitting for Medical Images.
Proceedings of the Advances in Visual Computing - 18th International Symposium, 2023

SILOP: An Automated Framework for Semantic Segmentation Using Image Labels Based on Object Perimeters.
Proceedings of the International Joint Conference on Neural Networks, 2023

Xel-FPGAs: An End-to-End Automated Exploration Framework for Approximate Accelerators in FPGA-Based Systems.
Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023

2022
ATLAS: An IoT Architecture and Secure Open-source Networking Stack for Anonymous Localization and Tracking Using Smartphones and Bluetooth Beacons.
CoRR, 2022

2021
BioNetExplorer: Architecture-Space Exploration of Biosignal Processing Deep Neural Networks for Wearables.
IEEE Internet Things J., 2021

BioNetExplorer: Architecture-Space Exploration of Bio-Signal Processing Deep Neural Networks for Wearables.
CoRR, 2021

2020
ApproxFPGAs: Embracing ASIC-Based Approximate Arithmetic Components for FPGA-Based Systems.
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

EMAP: A Cloud-Edge Hybrid Framework for EEG Monitoring and Cross-Correlation Based Real-time Anomaly Prediction.
Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

2019
Architectural-Space Exploration of Heterogeneous Reliability and Checkpointing Modes for Out-of-Order Superscalar Processors.
IEEE Access, 2019

XBioSiP: A Methodology for Approximate Bio-Signal Processing at the Edge.
Proceedings of the 56th Annual Design Automation Conference 2019, 2019

Heterogeneous Approximate Multipliers: Architectures and Design Methodologies.
Proceedings of the Approximate Circuits, Methodologies and CAD., 2019

Approximate Multi-Accelerator Tiled Architecture for Energy-Efficient Motion Estimation.
Proceedings of the Approximate Circuits, Methodologies and CAD., 2019

2018
Heterogeneous Reliability Modes with Efficient State Compression for Out-of-Order Superscalar Processors.
CoRR, 2018

Hardware and Software Techniques for Heterogeneous Fault-Tolerance.
Proceedings of the 24th IEEE International Symposium on On-Line Testing And Robust System Design, 2018

DeMAS: An efficient design methodology for building approximate adders for FPGA-based systems.
Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

Area-optimized low-latency approximate multipliers for FPGA-based hardware accelerators.
Proceedings of the 55th Annual Design Automation Conference, 2018

2017
Embracing approximate computing for energy-efficient motion estimation in high efficiency video coding.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017


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