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dc.contributor.refereeKlein, Rüdiger-
dc.contributor.authorBoussaada, Achraf-
dc.date.accessioned2019-04-09T12:17:42Z-
dc.date.available2019-04-09T12:17:42Z-
dc.date.issued2019-01-22-
dc.date.submitted2019-01-22-
dc.identifier.urihttps://opendata.uni-halle.de//handle/1981185920/13856-
dc.identifier.urihttp://dx.doi.org/10.25673/13757-
dc.description.abstractArtificial intelligence is a technology that‘s hugely controversial. Despite its potential, and for a long time, many people expressed their doubts about this technology and what it holds for us in the future (cited in D‘Onfro 2018 p.1-3; Novet 2018, p.1-3). But for the past few years AI kept growing exponentially and it‘s been implemented in numerous fields (cited in Artificial intelligence index, 2017, p.9-36), proving that it‘s a great asset that can yet open many other doors for a better everyday life (cited in Jahanzaib and Tarique, 2015, p.5). By leveraging the easy accessibility to AI documentation and frameworks this master thesis is continuity to my bachelor thesis with the goal of replacing classical image processing methods by an AI network that brings improvements to the project.eng
dc.language.isoeng-
dc.publisherHochschulbibliothek, Hochschule Merseburg-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectruck license plate recognitioneng
dc.subjectMachine Learningeng
dc.subjectclassical image processing methodseng
dc.subjectAI networkeng
dc.subject.ddc005-
dc.titleTunisian truck license plate recognition using an Android Application based on Machine Learning as a detection tooleng
dcterms.typeHochschulschrift-
dc.typeMaster Thesis-
dc.identifier.urnurn:nbn:de:gbv:542-1981185920-138563-
local.versionTypesubmittedVersion-
local.publisher.universityOrInstitutionHochschule Merseburg-
dc.identifier.ppn166301714X-
local.accessrights.dnbfree-
Enthalten in den Sammlungen:Informatik und Kommunikationssysteme

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