5 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.PF2024★ 5 cited
Acceleration and energy consumption optimization in cascading classifiers for face detection on low-cost ARM big.LITTLE asymmetric architectures
Alberto Corpas, Luis Costero, Guillermo Botella +3
This paper proposes a mechanism to accelerate and optimize the energy consumption of a face detection software based on Haar-like cascading classifiers, taking advantage of the fea…
cs.DC2017★ 2 cited
First Experiences Optimizing Smith-Waterman on Intel's Knights Landing Processor
Enzo Rucci, Carlos Garcia, Guillermo Botella +3
The well-known Smith-Waterman (SW) algorithm is the most commonly used method for local sequence alignments. However, SW is very computationally demanding for large protein databas…