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Multimedia data extraction and analysis tool: focus on video and image processing

2024Master thesis Open access
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datacite.subject.fosInformáticapt_PT
dc.contributor.advisorSilva, Fábio André Souto da
dc.contributor.authorBragança, João Miguel Teixeira
dc.date.accessioned2024-12-17T11:21:51Z
dc.date.available2024-12-17T11:21:51Z
dc.date.issued2024
dc.date.submitted2024
dc.description.abstractIn today’s digital landscape, the rapid growth of multimedia content, particularly from influencers, has created a critical need for advanced monitoring tools. Building on previous research in multimedia data analysis, this dissertation proposes the development of a tool for extracting and analysing multimedia data to detect violations in influencer-produced content. The tool leverages pre-trained models such as Whisper.AI for speech recognition, YOLOv8 for object detection, and EasyOCR for Optical Character Recognition (OCR). Additionally, sentiment analysis models are employed and tested, with YOLOv8 further trained for specific tasks such as logo detection, ensuring adaptability to various use cases. The objective of this dissertation is to design a versatile and customisable tool capable of performing precise content analysis, including object detection, speech transcription, OCR, sentiment analysis, image classification and logo detection. The solupt_PT
dc.identifier.tid203759940pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/26891
dc.language.isoengpt_PT
dc.subjectMultimedia data analysispt_PT
dc.subjectObject detectionpt_PT
dc.subjectSpeech recognitionpt_PT
dc.subjectSentiment analysispt_PT
dc.subjectContent monitoringpt_PT
dc.subjectLogo detectionpt_PT
dc.subjectImage Classificationpt_PT
dc.subjectOptical Character Recognitionpt_PT
dc.titleMultimedia data extraction and analysis tool: focus on video and image processingpt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameMestrado em Engenharia Informáticapt_PT

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