Bharath Srinivas Prabakaran
Orcid: 0000-0003-0557-2166
According to our database1,
Bharath Srinivas Prabakaran
authored at least 23 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
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