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Pregled bibliografske jedinice broj: 1191616

Emotions on Edge - the Dependence of Different Characteristics of the Convolutional Neural Network on the Number of Classes


Đokić, Kristian; Mandušić, Dubravka; Blašković, Lucija
Emotions on Edge - the Dependence of Different Characteristics of the Convolutional Neural Network on the Number of Classes // International Conference on Computer Science and Software Engineering (CSASE) - Proceedings
Duhok: Institute of Electrical and Electronics Engineers (IEEE), 2022. str. 224-229 doi:10.1109/CSASE51777.2022.9759761 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


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Naslov
Emotions on Edge - the Dependence of Different Characteristics of the Convolutional Neural Network on the Number of Classes

Autori
Đokić, Kristian ; Mandušić, Dubravka ; Blašković, Lucija

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
International Conference on Computer Science and Software Engineering (CSASE) - Proceedings / - Duhok : Institute of Electrical and Electronics Engineers (IEEE), 2022, 224-229

Skup
International Conference on Computer Science and Software Engineering CSASE 2022

Mjesto i datum
Duhok, Irak, 15.03.2022. - 17.03.2022

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
SoC , microcontroller , CNN , IoT , machine vision

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti



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Citiraj ovu publikaciju:

Đokić, Kristian; Mandušić, Dubravka; Blašković, Lucija
Emotions on Edge - the Dependence of Different Characteristics of the Convolutional Neural Network on the Number of Classes // International Conference on Computer Science and Software Engineering (CSASE) - Proceedings
Duhok: Institute of Electrical and Electronics Engineers (IEEE), 2022. str. 224-229 doi:10.1109/CSASE51777.2022.9759761 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Đokić, K., Mandušić, D. & Blašković, L. (2022) Emotions on Edge - the Dependence of Different Characteristics of the Convolutional Neural Network on the Number of Classes. U: International Conference on Computer Science and Software Engineering (CSASE) - Proceedings doi:10.1109/CSASE51777.2022.9759761.
@article{article, author = {\DJoki\'{c}, Kristian and Mandu\v{s}i\'{c}, Dubravka and Bla\v{s}kovi\'{c}, Lucija}, year = {2022}, pages = {224-229}, DOI = {10.1109/CSASE51777.2022.9759761}, keywords = {SoC , microcontroller , CNN , IoT , machine vision}, doi = {10.1109/CSASE51777.2022.9759761}, title = {Emotions on Edge - the Dependence of Different Characteristics of the Convolutional Neural Network on the Number of Classes}, keyword = {SoC , microcontroller , CNN , IoT , machine vision}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, publisherplace = {Duhok, Irak} }
@article{article, author = {\DJoki\'{c}, Kristian and Mandu\v{s}i\'{c}, Dubravka and Bla\v{s}kovi\'{c}, Lucija}, year = {2022}, pages = {224-229}, DOI = {10.1109/CSASE51777.2022.9759761}, keywords = {SoC , microcontroller , CNN , IoT , machine vision}, doi = {10.1109/CSASE51777.2022.9759761}, title = {Emotions on Edge - the Dependence of Different Characteristics of the Convolutional Neural Network on the Number of Classes}, keyword = {SoC , microcontroller , CNN , IoT , machine vision}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, publisherplace = {Duhok, Irak} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Emerging Sources Citation Index (ESCI)


Citati:





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