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Software Engineering And Distributed Computing In Image Processing Intelligent Systems: A Systematic Literature Review | ||
| Published in: | Prospective and trends in technology and skills for sustainable social development. Leveraging emerging technologies to construct the future: Proceedings of the 19th LACCEI International Multi-Conference for Engineering, Education and Technology |  |
| Date of Conference: | July 19-23, 2021 | |
| Location of Conference: | Virtual | |
| Authors: | Luis Jácome (Escuela Superior Politecnica del Litoral, ESPOL, EC) Mónica Villavicencio Cabezas (Escuela Superior Politecnica del Litoral, ESPOL, SV) Miguel Realpe (Escuela Superior Politecnica del Litoral, ESPOL, EC) José Benavides (Universidad Nacional de Loja, UNL, EC) | |
| Full Paper: | #175 | |
Abstract:Deep learning is experiencing an upward technology trend that is revolutionizing intelligent systems in several domains, such as image and speech recognition, machine translation, social network filtering, and the like. By reviewing a total of 80 studies reported from 2016 to 2020, the present article evaluates the application of software engineering to the field of intelligent image processing systems, it also offers insights about aspects related to distributed computing for this type of systems. Results indicate that several topics of software engineering are mostly applied when academics are involved in developing projects associated to this kind of intelligent systems. The findings provide evidences that Apache Spark is the most utilized distributed computing framework for image processing. In addition, Tensorflow is a popular framework used to build convolutional neural networks, which are the prevailing deep learning algorithms used in intelligent image processing systems. Also, among big cloud providers, Amazon Web Services is the preferred computing platform across the industry sectors, followed by Google cloud. | ||