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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 |