Emotions on Edge - the Dependence of Different Characteristics of the Convolutional Neural Network on the Number of Classes (CROSBI ID 717197)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Đokić, Kristian ; Mandušić, Dubravka ; Blašković, Lucija
engleski
Emotions on Edge - the Dependence of Different Characteristics of the Convolutional Neural Network on the Number of Classes
Machine learning is most often associated with powerful computers, but lately, it is increasingly present on both microcontrollers and systems on a chip. Initially, simple machine learning algorithms were used on these platforms, but today we already see high-resolution cameras and convolutional neural networks used to process camera data. Models for such systems are prepared on large and powerful computers, but previously trained neural networks could be copied and used on microcontrollers and systems on a chip. This paper aims to measure the performance and characteristics of systems on a chip in which a convolution neural network for recognizing facial emotions is implemented. A different number of emotions are used to determine the impact of this change on performance, and the effect of quantization on performance and model size is also analyzed.
SoC , microcontroller , CNN , IoT , machine vision
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Podaci o prilogu
224-229.
2022.
objavljeno
10.1109/CSASE51777.2022.9759761
Podaci o matičnoj publikaciji
International Conference on Computer Science and Software Engineering (CSASE) - Proceedings
Duhok: Institute of Electrical and Electronics Engineers (IEEE)
Podaci o skupu
International Conference on Computer Science and Software Engineering CSASE 2022
predavanje
15.03.2022-17.03.2022
Duhok, Irak
Povezanost rada
Informacijske i komunikacijske znanosti