dc.contributor.author | Jácome, Luis | |
dc.contributor.author | Villavicencio Cabezas, Mónica | |
dc.contributor.author | Realpe, Miguel | |
dc.contributor.author | Benavides, José | |
dc.date.accessioned | 2021-08-17T03:07:59Z | |
dc.date.accessioned | 2022-02-22T12:15:09Z | |
dc.date.available | 2021-08-17T03:07:59Z | |
dc.date.available | 2022-02-22T12:15:09Z | |
dc.date.issued | 2021-07 | |
dc.identifier.isbn | 978-958-52071-8-9 | |
dc.identifier.issn | 2414-6390 | |
dc.identifier.other | http://laccei.org/LACCEI2021-VirtualEdition/meta/FP175.html | |
dc.identifier.uri | http://dx.doi.org/10.18687/LACCEI2021.1.1.175 | |
dc.identifier.uri | http://axces.info/handle/10.18687/20210101_175 | |
dc.description.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. | en_US |
dc.language.iso | English | en_US |
dc.publisher | LACCEI Inc. | en_US |
dc.rights | LACCEI License | |
dc.rights.uri | https://laccei.org/blog/copyright-laccei-papers/ | |
dc.subject | Image processing | en_US |
dc.subject | software engineering | en_US |
dc.subject | deep learning | en_US |
dc.subject | intelligent vision systems | en_US |
dc.subject | cloud computing | en_US |
dc.title | Software Engineering and Distributed Computing in image processing intelligent systems: a systematic literature review | |
dc.type | Article | en_US |
dc.description.country | Ecuador | en |
dc.description.institution | Escuela Superior Politecnica del Litoral, ESPOL | en |
dc.description.track | I.T, Telecom, Soft. Eng, IoT, Ind. 4.0, Forensic Informatics, Security, Cybersecurity and Comp tools | en |
dc.journal.referato | peerReview | |