Comparison of Object Detection Algorithms for the Task of Person Detection on Jetson TX2 NX Platform

Byzkrovnyi, Oleksandr; Smelyakov, Kyrylo; Chupryna, Anastasiya; Lanovyy, Oleksiy

doi:10.1109/estream61684.2024.10542592

2024 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream) 2024

DOI: 10.1109/estream61684.2024.10542592

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Comparison of Object Detection Algorithms for the Task of Person Detection on Jetson TX2 NX Platform

Oleksandr Byzkrovnyi,

Kyrylo Smelyakov,

Anastasiya Chupryna

et al.

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2024

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Cited by 1 publication

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A Review of Recent Hardware and Software Advances in GPU-Accelerated Edge-Computing Single-Board Computers (SBCs) for Computer Vision

Iqbal,

Davies,

Perez

2024

Sensors

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Computer Vision (CV) has become increasingly important for Single-Board Computers (SBCs) due to their widespread deployment in addressing real-world problems. Specifically, in the context of smart cities, there is an emerging trend of developing end-to-end video analytics solutions designed to address urban challenges such as traffic management, disaster response, and waste management. However, deploying CV solutions on SBCs presents several pressing challenges (e.g., limited computation power, inefficient energy management, and real-time processing needs) hindering their use at scale. Graphical Processing Units (GPUs) and software-level developments have emerged recently in addressing these challenges to enable the elevated performance of SBCs; however, it is still an active area of research. There is a gap in the literature for a comprehensive review of such recent and rapidly evolving advancements on both software and hardware fronts. The presented review provides a detailed overview of the existing GPU-accelerated edge-computing SBCs and software advancements including algorithm optimization techniques, packages, development frameworks, and hardware deployment specific packages. This review provides a subjective comparative analysis based on critical factors to help applied Artificial Intelligence (AI) researchers in demonstrating the existing state of the art and selecting the best suited combinations for their specific use-case. At the end, the paper also discusses potential limitations of the existing SBCs and highlights the future research directions in this domain.

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A Review of Recent Hardware and Software Advances in GPU-Accelerated Edge-Computing Single-Board Computers (SBCs) for Computer Vision

Iqbal,

Davies,

Perez

2024

Sensors

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show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Comparison of Object Detection Algorithms for the Task of Person Detection on Jetson TX2 NX Platform

Cited by 1 publication

References 17 publications

A Review of Recent Hardware and Software Advances in GPU-Accelerated Edge-Computing Single-Board Computers (SBCs) for Computer Vision

A Review of Recent Hardware and Software Advances in GPU-Accelerated Edge-Computing Single-Board Computers (SBCs) for Computer Vision

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