Franck Yonga
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Research Areas
Biography and Research Information
OverviewAI-generated summary
Franck Yonga's research centers on the development of embedded platforms for image processing and autonomous driving systems. He has published work on RazorCam, an embedded platform designed for image processing, and RazorCar, an FPGA-based prototyping platform for autonomous driving systems. Yonga's work involves the application of hardware acceleration techniques to complex computational tasks. His scholarship metrics include an h-index of 6, with 16 total publications and 76 citations. He has collaborated with Michael Mefenza at the University of Arkansas at Fayetteville on two shared publications, indicating an active research network within his institution.
Metrics
- h-index: 6
- Publications: 16
- Citations: 77
Selected Publications
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RazorCam: Embedded Platform for Image Processing (2025)
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High-level synthesis of on-chip multiprocessor architectures based on answer set programming (2018)
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Component interconnect and data access interface for embedded vision applications (2015)
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Efficient network clustering for traffic reduction in embedded smart camera networks (2015)
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ASP-Based Encoding Model of Architecture Synthesis for Smart Cameras in Distributed Networks (2015)
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Automatic UVM Environment Generation for Assertion-Based and Functional Verification of SystemC Designs (2014)
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Self-Coordinated Target Assignment and Camera Handoff in Distributed Network of Embedded Smart Cameras (2014)
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Reconfigurable Architectures for Distributed Smart Cameras (2014)
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A framework for rapid prototyping of embedded vision applications (2014)
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ACM HotMobile 2013 poster (2013)
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A hardware/software prototyping system for driving assistance investigations (2013)
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RazorCam: A Prototyping Environment for Video Communication (2012)2 citations OpenAlex
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Improving video communication in distributed smart camera systems through ROI-based video analysis and compression (2012)
Collaboration Network
Top Collaborators
- A hardware/software prototyping system for driving assistance investigations
- Automatic UVM Environment Generation for Assertion-Based and Functional Verification of SystemC Designs
- A framework for rapid prototyping of embedded vision applications
- Reconfigurable Architectures for Distributed Smart Cameras
- High-level synthesis of on-chip multiprocessor architectures based on answer set programming
Showing 5 of 13 shared publications
- A hardware/software prototyping system for driving assistance investigations
- Automatic UVM Environment Generation for Assertion-Based and Functional Verification of SystemC Designs
- A framework for rapid prototyping of embedded vision applications
- Reconfigurable Architectures for Distributed Smart Cameras
- Efficient network clustering for traffic reduction in embedded smart camera networks
Showing 5 of 11 shared publications
- A framework for rapid prototyping of embedded vision applications
- Self-Coordinated Target Assignment and Camera Handoff in Distributed Network of Embedded Smart Cameras
- A framework for rapid prototyping of embedded vision applications
- Self-Coordinated Target Assignment and Camera Handoff in Distributed Network of Embedded Smart Cameras
- Reconfigurable Architectures for Distributed Smart Cameras
- Efficient network clustering for traffic reduction in embedded smart camera networks
- Self-Coordinated Target Assignment and Camera Handoff in Distributed Network of Embedded Smart Cameras
- A hardware/software prototyping system for driving assistance investigations
- A hardware/software prototyping system for driving assistance investigations
- A hardware/software prototyping system for driving assistance investigations
- Improving video communication in distributed smart camera systems through ROI-based video analysis and compression
- High-level synthesis of on-chip multiprocessor architectures based on answer set programming
- High-level synthesis of on-chip multiprocessor architectures based on answer set programming
- High-level synthesis of on-chip multiprocessor architectures based on answer set programming
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