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Detail publikace
JURÁNEK, L. ŠŤASTNÝ, J. ŠKORPIL, V. JUNEK, L.
Originální název
Acceleration of Server-side Image Processing by Client-side Pre-processing in Web Application Environment
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
The goal of this paper is to verify whether the use of client-side TensorFlow.js, a WebGL-accelerated JavaScript library for machine learning, can accelerate the processing of common photos by computer vision cloud services, such as detection and recognition of specific features like age, sex, expression or specific people in the image. This acceleration is based on pre-processing the input image, namely detecting human faces, which greatly changes the amount of input data that need to be uploaded to the cloud service and thus the amount of uploaded data compared to the original photograph. The upload speed of Internet connection often is, in the case of computer vision cloud services, the bottleneck of the whole system. That´s why decreasing the amount of uploaded data in time shorter than the difference between the total of upload and cloud service processing time of the original and the pre-processed image leads to acceleration.
Klíčová slova
cloud; face detection; image preprocessing; TenrFlow; WebGL
Autoři
JURÁNEK, L.; ŠŤASTNÝ, J.; ŠKORPIL, V.; JUNEK, L.
Vydáno
1. 7. 2019
Nakladatel
IEEE
Místo
Budapešť, Hungary
ISBN
978-1-7281-1864-2
Kniha
42nd International Conference on Telecommunications and Signal Processing (TSP 2019)
Strany od
127
Strany do
130
Strany počet
4
URL
https://ieeexplore.ieee.org/document/8769104
BibTex
@inproceedings{BUT158145, author="Luboš {Juránek} and Jiří {Šťastný} and Vladislav {Škorpil} and Lukáš {Junek}", title="Acceleration of Server-side Image Processing by Client-side Pre-processing in Web Application Environment", booktitle="42nd International Conference on Telecommunications and Signal Processing (TSP 2019)", year="2019", pages="127--130", publisher="IEEE", address="Budapešť, Hungary", doi="10.1109/TSP.2019.8768889", isbn="978-1-7281-1864-2", url="https://ieeexplore.ieee.org/document/8769104" }