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http://dx.doi.org/10.17703/IJACT.2022.10.2.246

Comparison of On-Device AI Software Tools  

Song, Hong-Jong (4th Industrial ICT Team National Radio Research Agency)
Publication Information
International Journal of Advanced Culture Technology / v.10, no.2, 2022 , pp. 246-251 More about this Journal
Abstract
As the number of data and devices explodes, centralized data processing and AI analysis have limitations due to the load on the network and cloud. On-device AI technology can provide intelligent services without overloading the network and cloud because the device itself performs AI models. Accordingly, the need for on-device AI technology is emerging. Many smartphones are equipped with On-Device AI technology to support the use of related functions. In this paper, we compare software tools that implement On-Device AI.
Keywords
On-Device; AI; Tool; Machine Learning;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
연도 인용수 순위
1 Y. Lee, "Analysis of Automatic Machine Learning Solution Trends of Startups," Vol.8, No.2, International Journal of Advanced Culture Technology, 2020, https://doi.org/10.17703/IJACT.2020.8.2.297.   DOI
2 Y. Lee, "Analysis on trends of machine learning-as-a-service," Vol. 6, No. 4, International Journal of Advanced Culture Technology, 2018, https://doi.org /10.17703//IJACT2018.6.4.303.   DOI
3 On-Device Artificial Intelligence: A Game Changer, https://innodata.com/on-device-artificial-intelligence/
4 S. Lee, "Trend of On-Device AI Hardware and Software Technology Development," Weekly Technology Trend, No. 2028, 2021.
5 ML Kit, https://developers.google.com/ml-kit.
6 CoreML, https://developer.apple.com/machine-learning/core-ml/.
7 TensorRT, https://developer.nvidia.com/tensorrt.
8 Arm Compute Library, https://www.arm.com/technologies/compute-library.
9 AI Model Efficiency Toolkit(AIMET), https://developer.qualcomm.com/software/ai-model-efficiency-toolkit.