Performance Optimization of Machine Learning-Driven Image Recognition Algorithms for iOS Mobile Platforms

Today., mobile devices play an important role in the daily life of every person., without which many can no longer imagine their lives. One of the key technologies leading to significant benefits for mobile applications is machine learning. Optimization of machine learning algorithms for mobile devices is an urgent and important task., it is aimed at developing and applying methods that will effectively use the limited computing resources of mobile devices. The paper discusses various ways to optimize image recognition algorithms on mobile devices., such as quantization and compression of models., optimization of initial calculations. In addition to ways to optimize the machine learning model itself., various libraries and tools for using this technology on mobile devices are also being considered. Each of the described methods has its advantages and disadvantages., and therefore., in the results of the work., it is proposed to use not only a combination of the described options., but also an additional method of parallelization of image processing processes.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1109/summa64428.2024.10803881
Citations
1
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.25
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article

Performance Optimization of Machine Learning-Driven Image Recognition Algorithms for iOS Mobile Platforms

Ibragim Mamadaev, Muslim Mamadaev
1 citations
Brain Tumor Detection and Classification
0.25
article

Performance Optimization of Machine Learning-Driven Image Recognition Algorithms for iOS Mobile Platforms

Ibragim Mamadaev, Muslim Mamadaev
article en
1 citations

Abstract

Today., mobile devices play an important role in the daily life of every person., without which many can no longer imagine their lives. One of the key technologies leading to significant benefits for mobile applications is machine learning. Optimization of machine learning algorithms for mobile devices is an urgent and important task., it is aimed at developing and applying methods that will effectively use the limited computing resources of mobile devices. The paper discusses various ways to optimize image recognition algorithms on mobile devices., such as quantization and compression of models., optimization of initial calculations. In addition to ways to optimize the machine learning model itself., various libraries and tools for using this technology on mobile devices are also being considered. Each of the described methods has its advantages and disadvantages., and therefore., in the results of the work., it is proposed to use not only a combination of the described options., but also an additional method of parallelization of image processing processes.

Bauman Moscow State Technical University (RU)
Openalex Percentile: Top 40%
Brain Tumor Detection and Classification
0.25
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Performance Optimization of Machine Learning-Driven Image Recognition Algorithms for iOS Mobile Platforms — Ibragim Mamadaev, Muslim Mamadaev · (2024) | TGRS Research Map | TGRS