Alpha-Bit: An Android App for Enhancing Pattern Recognition using CNN and Sequential Deep Learning
This research paper introduces Alpha-Bit, an Android application pioneering Optical Character Recognition (OCR) through cutting-edge deep learning models, including Convolutional Neural Networks (CNNs) and Sequential networks. With a core focus on enhancing educational accessibility and quality, Alpha-Bit specifically targets foundational elements of the English language—alphabets and numbers. Beyond conventional OCR applications, Alpha-Bit distinguishes itself by offering guided instruction and individual progress reports, providing a nuanced and tailored educational experience. Significantly, this work extends beyond technological innovation; Alpha-Bit’s potential impact encompasses addressing educational inequalities, contributing to sustainability goals, and advancing the achievement of Sustainable Development Goal 4 (SDG 4). By democratizing education through innovative OCR technologies, Alpha-Bit emerges as a transformative force with the capacity to revolutionize learning experiences, making quality education universally accessible and empowering learners across diverse socio-economic backgrounds.
Authors
- Gobi Ramasamy (ORCID: https://orcid.org/0000-0002-0176-5414)
- R. Arokia Paul Rajan (ORCID: https://orcid.org/0000-0001-7481-9308)
- Antoine Bagula (ORCID: https://orcid.org/0000-0003-0774-5251)
- Priyadharshini Rengasamy
Institutions
- Christ University (IN)
- University of the Western Cape (ZA)
Publication Details
- Published
- 2024-10-21
- DOI
- https://doi.org/10.23919/ituk62727.2024.10772809
- Primary Topic
- IoT-based Smart Home Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00