Image Detection in Low-Quality Videos

dc.contributorCipolla, Lautaro. Universidad Siglo 21. Vicerrectorado de Innovación, Investigación y Posgrado. Referente de Repositorio Institucional; Argentina.
dc.contributor.authorLópez De Luise, Daniela
dc.contributor.authorBenitez, Micaela Antonella
dc.contributor.authorMencia Aramis, Oscar
dc.contributor.authorPark Jin Sung
dc.contributor.authorBordon Sbardella Felix Raul
dc.contributor.authorRíos Anahí Ailén
dc.contributor.authorHoferek, Silvia
dc.date.accessioned2025-11-10T14:08:08Z
dc.date.available2025-11-10T14:08:08Z
dc.date.issued2025
dc.descriptionPublished in: 2024 IEEE Biennial Congress of Argentina (ARGENCON) Date of Conference: 18-20 September 2024 Date Added to IEEE Xplore: 04 November 2024 ISBN Information: Electronic ISBN:979-8-3503-6593-1 Print on Demand(PoD) ISBN:979-8-3503-6594-8 DOI: 10.1109/ARGENCON62399.2024.10735809 Publisher: IEEE Conference Location: San Nicolás de los Arroyos, Argentina
dc.description.abstractThis article aims to describe recent findings on a prototype for assisting blind people. To improve its functioning the main approach is to build an intelligent system composed by Machine Learning of several models to detect and recognize multiple objects. The scope of this activity includes efficiency assessment, video data compilation, image segmentation, Data Mining processing, and tagging. This work also evaluates and depicts certain techniques and approaches to be applied to create models with high pattern detection efficiency. The algorithm must be light as well as quick, in order to be used in standard cell phones to assist blind people and provide meaningful information to the user as well as a small analysis of the results. Furthermore this study outlines specific methods and strategies employed to develop highly efficient models for pattern recognition.
dc.description.filFil: Hoferek, Silvia. Universidad Siglo 21. Vicerrectorado de Innovación, Investigación y Posgrado. Secretaría de Investigación. Decanato de Ciencias, Aplicadas; Argentina.
dc.formatapplication/pdf
dc.identifier.urihttps://repositorio.21.edu.ar/handle/ues21/29595
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.rights.licenseCC0 1.0 Universalen
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/
dc.titleImage Detection in Low-Quality Videos
dc.typeinfo:eu-repo/semantics/bookPart
dc.type.snrdinfo:ar-repo/semantics/parte de libro
dc.type.versioninfo:eu-repo/semantics/publishedVersion

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