2021/07/19 by R. Ildar, Ildar, R. · 1 voice
Computer Science · Engineering · Neuroscience · Social Sciences · #Advanced Computing and Algorithms #Brain Tumor Detection and Classification #Distributed #FOS: Computer and information sciences #Optical Systems and Laser Technology #Parallel #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.2107.12148
arxiv created 2021/07/19 · openalex publication_date 2021/07/19 · arxiv published 2021/07/19 · arxiv updated 2021/07/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This manuscript provides a review of methods for increasing the frame per second of single-board computers. The main emphasis is on the Jetson family of single-board computers from Nvidia Company, due to the possibility of using a graphical interface for calculations. But taking into account the popular low-cost segment of single-board computers as RaspberryPI family, BananaPI, OrangePI, etc., we also provided an overview of methods for increasing the frame per second without using a Graphics Processing Unit. We considered frameworks, software development kit, and various libraries that can be used in the process of increasing the frame per second in single-board computers. Finally, we tested the presented methods for the YOLOv4-tiny model with a custom dataset on the Jetson nano and presented the results in the table.