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Movementor - Your Personal Workout Guide

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dc.contributor.author Manathunga, Ramitha
dc.date.accessioned 2025-06-16T03:59:55Z
dc.date.available 2025-06-16T03:59:55Z
dc.date.issued 2024
dc.identifier.citation Manathunga, Ramitha (2024) Movementor - Your Personal Workout Guide. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 20200910
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/2552
dc.description.abstract "This research covers the underrated issue of incorrect workout techniques and the absence of corrective feedback during workout sessions, which often result in injuries and strain. This research introduces a hybrid model known as the Long-term Recurrent Convolutional Network (LRCN), which takes advantage of both Convolutional Neural Networks (CNN) and Long ShortTerm Memory (LSTM) to enhance pose detection. This approach aims to detect workouts and provide real-time feedback on intense workouts ensuring safe and effective exercise execution." en_US
dc.language.iso en en_US
dc.subject LRCN en_US
dc.subject Motion Recognition en_US
dc.subject CNN en_US
dc.title Movementor - Your Personal Workout Guide en_US
dc.type Thesis en_US


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