Bharath Srinivas Prabakaran
Orcid: 0000-0003-0557-2166
According to our database1,
Bharath Srinivas Prabakaran
authored at least 24 papers
between 2017 and 2024.
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Bibliography
2024
UnbiasedNets: a dataset diversification framework for robustness bias alleviation in neural networks.
Mach. Learn., May, 2024
A Novel Weakly Supervised Semantic Segmentation Ensemble Framework for Medical Imaging.
Proceedings of the International Joint Conference on Neural Networks, 2024
2023
Exploring Weakly Supervised Semantic Segmentation Ensembles for Medical Imaging Systems.
CoRR, 2023
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
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
Proceedings of the 56th Annual Design Automation Conference 2019, 2019
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
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