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Federico García-Rial

dblp:206/1486 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2017
0000-0002-8548-1768ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
GPUs and heterogeneous computing · 100%
Computer graphics and multimedia
1 paper
Image and video processing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing
real-time image processing		 0.312017
Real-Time GPU-Based Image Processing for a 3-D THz Radar · IEEE Trans. Parallel Distributed Syst. 2017
GPUs and heterogeneous computing › GPU-accelerated data processing
GPU image processing		 0.312017
Real-Time GPU-Based Image Processing for a 3-D THz Radar · IEEE Trans. Parallel Distributed Syst. 2017
GPUs and heterogeneous computing
GPU computing		 0.112017
Real-Time GPU-Based Image Processing for a 3-D THz Radar · IEEE Trans. Parallel Distributed Syst. 2017

Methods — techniques the papers use, named apart from their topics

CUDA · 0.6
YearPublicationVenuePosition
2017 Real-Time GPU-Based Image Processing for a 3-D THz Radar
abstract
A real-time image processing algorithm, using a GPU with NVIDIA's CUDA technology, for a 3-D through-clothes detection radar in the THz band has been developed. Traditional CPU-based architectures lack the computing power and parallelization needed to meet the image refresh rates imposed by the radar's scanning. This solution presents a low-cost and flexible alternative that allows image refresh at a rate of more than 8 fps for images composed of 6,000 pixels, corresponding to a scanned area of 50x90 cm2. The performance of this code has been profiled, with comparison against a previous CPU-executed version, and some optimizations that would enable even faster refresh have been analyzed.
Federico García-Rial, Luis Ubeda-Medina, Jesús Grajal
 IEEE Trans. Parallel Distributed Syst.1