Convergence property of Nesterov-accelerated adaptive moment estimation with safety helmet detection and classification in smart industry application
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Issued Date
2024-01-01
Resource Type
ISSN
01704214
eISSN
10991476
Scopus ID
2-s2.0-85193509226
Journal Title
Mathematical Methods in the Applied Sciences
Rights Holder(s)
SCOPUS
Bibliographic Citation
Mathematical Methods in the Applied Sciences (2024)
Suggested Citation
Jirakitpuwapat W., Dubey P., Prasertsuk N., Phanthong C., Tritham C., Tritham C., Chandharakool S., Tharathep C., Soontornpipit P. Convergence property of Nesterov-accelerated adaptive moment estimation with safety helmet detection and classification in smart industry application. Mathematical Methods in the Applied Sciences (2024). doi:10.1002/mma.10174 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/98486
Title
Convergence property of Nesterov-accelerated adaptive moment estimation with safety helmet detection and classification in smart industry application
Corresponding Author(s)
Other Contributor(s)
Abstract
We propose a technique for first-order gradient-based optimization of stochastic objective functions called Nesterov-accelerated adaptive moment assessment, which makes use of dynamic evaluations of lower-order moments. The adaptive moment assessment and the Nesterov acceleration gradient are combined. Consequently, it has perks, and this technique is convenient to use, numerically economical, memory-light, and very well-suited for challenges with massive amounts of information and characteristics. Additionally, we investigate the algorithm's convergence characteristics and propose a conservative constraint on the convergence rate. Finally, we employ this technique for the detection and classification of safety helmets.