Gestu Slide Master

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dc.contributor.author Nabiha Sumar, 01-134202-052
dc.contributor.author Esha Amir, 01-134202-019
dc.date.accessioned 2024-07-22T05:16:03Z
dc.date.available 2024-07-22T05:16:03Z
dc.date.issued 2024
dc.identifier.uri http://hdl.handle.net/123456789/17562
dc.description Supervised by Dr. Sabina Akhtar en_US
dc.description.abstract Presentations often play a pivotal role in various professional domains, necessitating effective delivery and engagement. However, somehow the existing presentation tools often rely on traditional input methods to navigate and make the slides functional which might somehow hinder the accessibility and interaction of the presenter with the audience. In response to this, GestuSlide Master emerged as a cutting-edge technology that is an interactive presentation tool, harnessing state-of-the-art computer vision and gesture recognition technologies. GestuSlide Master is developed with the state-of-the-art library i.e. OpenCV and Tensorflow that has a mission to pioneer an innovative and assistive technology solution that can transcend the constraints of input devices. Its main objectives include developing an advanced presentation system enabling intuitive hand gestures for seamless delivery in the educational and cooperate world. This multi-gesture-supported system not only enables users to navigate through the slides seamlessly but also gives the ability to annotate, draw, and highlight the important points in the presentation. GestuSlide Master offers comprehensive user guidance through various resources in the shape of blogs and user guides encapsulated on the website to ensure a smooth and effective system utilization of the system. en_US
dc.language.iso en en_US
dc.publisher Computer Sciences en_US
dc.relation.ispartofseries BS(CS);P-02208
dc.subject Gestu en_US
dc.subject Slide en_US
dc.subject Master en_US
dc.title Gestu Slide Master en_US
dc.type Project Reports en_US


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