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@article{181932,
        author = {HUZEFA USMAAN SHAIKH and Vishakha Nayak and Savidhan Ambhore and Khalid Siddiqui},
        title = {Automated Document Classification and Sorting Using Template Matching},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {410-414},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=181932},
        abstract = {Handling large quantities of documents manually often results in mistakes and reduced efficiency, particularly when documents appear alike but fall into different categories. This challenge can be addressed through template matching. Template matching helps automatically detect the document type and categorize it into appropriate databases. Technologies like Optical Character Recognition (OCR), Artificial Intelligence (AI), and Natural Language Processing (NLP) are employed to enhance document handling by improving accuracy, saving time, and streamlining storage. The system is built using Python, Tesseract OCR, Firebase (Supabase), and Node.js, providing a reliable and scalable document management solution.},
        keywords = {Template Matching, Tesseract OCR, NLP, Sorting, Node js, Supabase,},
        month = {July},
        }