• Dr.Saroja.T.V
• Prathamesh Mayekar
• Aditi Barhate
• Diksha Telgote

: Convolutional Neural Networks (CNNs) and deep learning have found a wide range of applications across various fields due to their ability to effectively learn from large amounts of data and extract meaningful features. In this Project we have used the power of CNN and the Google Vision Api to create a comprehensive model which can understand the text, numbers, and special characters written in form of handwritten paragraph and convert this handwritten paragraph into digital text. This is accomplished by first uploading the image of the handwritten paragraph and then giving it as an input to the trained CNN model and the finally getting the digital text as an output, which can be copied from the clipboard present on the user interface. This project also focuses on the data security part where user’s sensitive data in stored in encrypted form in the database. Also, we have created an end-to-end pipeline using which all users can track their upload history and also give a feedback score to the output given by the model.

CNN, handwritten text, data security.

"PARAGRAPH READER USING CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.143-153, July-2024, Available :http://www.jetir.org/papers/JETIRGK06019.pdf

"PARAGRAPH READER USING CNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. pp143-153, July-2024, Available at : http://www.jetir.org/papers/JETIRGK06019.pdf