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@article{170161,
        author = {Kavita Dige and Sunit Dhopte and Akshada Padale and Shreya Walde},
        title = {SA2SAS: Smart Assisted Archaeological Script Analysis System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {3773-3777},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=170161},
        abstract = {The Smart Assisted Archaeological Script Analysis System, relies on the innovative approaches of image processing and machine learning to automate the study of old inscriptions. Old methods of analysing an inscription consume a lot of time and effort. This system streamlines critical phases such as image enhancement, extraction, and classification using deep learning models in order to deliver faster and more accurate analyses. This way, the system will allow archaeologists to work faster and with more accuracy while saving the precious information about history. The new approach helps not only in archaeological research but also gives light toward a better understanding of ancient civilizations and their writing systems.},
        keywords = {Machine learning, deep learning, image recognition and classification, ancient script recognition, Convolutional neural network.},
        month = {December},
        }