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@article{192090,
        author = {Linju A C and Deepashree N G and Lipi T U and Mokshith P B and Nibin Thomas},
        title = {Handwritten Notes Converter For Smart Digitization And Organization},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {187-192},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192090},
        abstract = {The Text Recognition is a mobile application designed to convert images and handwritten notes into editable, organized, and multilingual digital text. Built with React Native and Expo, the application integrates Google Cloud Vision API for Optical Character Recognition (OCR), Firebase for cloud synchronization, and Hugging Face APIs for text summarization and question generation. It further enhances accessibility through multi-language translation and text-to-speech (TTS) features using Expo Speech and Google Translation APIs. The app enables users to capture or import images, extract and edit text, categorize notes by subject, and export or share them as formatted PDFs. With offline caching, real-time synchronization, and a user-centric interface, it ensures reliability and seamless operation even in low-connectivity environments. The project demonstrates proficiency in cross-platform mobile development, API integration, AI model deployment, and cloud database management, addressing modern productivity and study assistance needs for students and professionals alike.},
        keywords = {Mobile Application, Optical Character Recognition (OCR), React Native, Firebase Firestore, Cloud Synchronization, Text Summarization, Question Generation, Google Cloud Vision API, Hugging Face API, Multi-language Translation, Text-to-Speech (TTS), Expo Framework, AI-based Study Assistant, Digital Note Management.},
        month = {January},
        }