E3S Web Conf.
Volume 229, 2021The 3rd International Conference of Computer Science and Renewable Energies (ICCSRE’2020)
|Number of page(s)||4|
|Published online||25 January 2021|
FPGA-based Hardware Acceleration for SVM Machine Learning Algorithm
Laboratory of Energy Engineering, Materials and Systems, National School of Applied Sciences, Ibn Zohr University, Agadir, Morocco
2 National School of Applied Sciences, Cady Ayad University, Marrakech, Morocco
* Corresponding author: firstname.lastname@example.org
object recognition algorithms are both large consumers of computing power and memory which affects the quality and performance especially when it comes to large image datasets, in this paper we propose an algorithm for fruit/plant recognition that we will accelerate it using the PYNQ Board to evaluate the execution time and the accuracy of the classifier.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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