TY - GEN
T1 - A Computational Comparative Analysis Between Nvidia Jetson Nano and Raspberry Pi CM4 for the Classification of White Asparagus with SVM
AU - Ruiz, Edgar
AU - Ortiz, Manuel
AU - Vinces, Leonardo
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - The following study proposes to analyze and compare the computational response provided by the Single Board Computers (SBC) Raspberry Pi CM4 and Nvidia Jetson Nano because those are important elements in machine learning applications and implementation of automated systems. Both were chosen due to their similar specifications to achieve a fair comparison. For the development of this research, an algorithm was implemented with a Support Vector Machine to be able to compare the performance in real-time of both computers based on performance metrics such as execution time, algorithm accuracy, CPU performance, and temperature. To validate results, there is a database of 2186 white asparagus images, which were classified based on attributes such as length, curvature, diameter, and purple hue. These attributes are established by the Peruvian Asparagus and Vegetable Institute (IPEH) in the Peruvian Technical Standard to ensure the quality of fresh asparagus for export. The algorithm has been designed to classify asparagus according to this technical standard.
AB - The following study proposes to analyze and compare the computational response provided by the Single Board Computers (SBC) Raspberry Pi CM4 and Nvidia Jetson Nano because those are important elements in machine learning applications and implementation of automated systems. Both were chosen due to their similar specifications to achieve a fair comparison. For the development of this research, an algorithm was implemented with a Support Vector Machine to be able to compare the performance in real-time of both computers based on performance metrics such as execution time, algorithm accuracy, CPU performance, and temperature. To validate results, there is a database of 2186 white asparagus images, which were classified based on attributes such as length, curvature, diameter, and purple hue. These attributes are established by the Peruvian Asparagus and Vegetable Institute (IPEH) in the Peruvian Technical Standard to ensure the quality of fresh asparagus for export. The algorithm has been designed to classify asparagus according to this technical standard.
KW - Asparagus
KW - Image processing
KW - Jetson Nano
KW - Raspberry Pi CM4
KW - SBC
KW - Support Vector Machine
UR - https://www.scopus.com/pages/publications/85135098241
U2 - 10.1007/978-3-031-08545-1_49
DO - 10.1007/978-3-031-08545-1_49
M3 - Contribución a la conferencia
AN - SCOPUS:85135098241
SN - 9783031085444
T3 - Smart Innovation, Systems and Technologies
SP - 506
EP - 513
BT - Proceedings of the 7th Brazilian Technology Symposium, BTSym 2021 - Emerging Trends in Systems Engineering Mathematics and Physical Sciences
A2 - Iano, Yuzo
A2 - Saotome, Osamu
A2 - Kemper Vásquez, Guillermo Leopoldo
A2 - Cotrim Pezzuto, Claudia
A2 - Arthur, Rangel
A2 - Gomes de Oliveira, Gabriel
PB - Springer Science and Business Media Deutschland GmbH
T2 - 7th Brazilian Technology Symposium, BTSym 2021
Y2 - 8 November 2021 through 10 November 2021
ER -