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Signflow Translator App

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dc.contributor.author Toheed Ul Haq, 01-134221-082
dc.contributor.author Rana Amanullah, 01-134221-067
dc.date.accessioned 2026-08-21T05:21:26Z
dc.date.available 2026-08-21T05:21:26Z
dc.date.issued 2025
dc.identifier.uri http://hdl.handle.net/123456789/21623
dc.description Supervised by Dr. Erum Ashraf en_US
dc.description.abstract The Sign Flow Translator App is designed to bridge the communication gap between the deaf and hearing communities by translating Pakistani Sign Language ( PSL ) gestures into text in real time. The SignFlow Translator App aims to bridge this gap by providing a real-time, AI-powered sign language translation system. Leveraging Computer Vision, the application translates sign language gestures into grammatically correct text. Built using modern frameworks such as Flutter for mobile application development and Django for backend, the app supports multi-modal inputs through live webcam feeds. The project adopts an Agile development methodology, ensuring iterative improvements across data collection, model training, and UI/UX design. Though limited in initial scope to text-only and one-way communication. SignFlow sets a strong foundation for scalable and accessible sign language solutions across healthcare, education, and public service sectors. en_US
dc.language.iso en en_US
dc.publisher Computer Sciences en_US
dc.relation.ispartofseries BS(CS);P-3981
dc.subject Signflow en_US
dc.subject Translator en_US
dc.subject App en_US
dc.title Signflow Translator App en_US
dc.type Project Reports en_US


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