Published Paper Details:

As everything becomes increasingly digitised in this rapidly evolving world, exchanging information plays a crucial role in any work. However, sometimes we may not have access to a computer or other electronic device to create a document, and instead use pen and paper. Unfortunately, people may not be able to understand everything that is expressed on paper due to factors such as poor penmanship. To address this issue, we are developing a platform that can convert handwritten text into editable text. Our primary goal is to classify words directly and segment characters using a convolutional neural network (CNN). Long-term memory networks (LSTM) are also used to create bounding boxes for each character, which are divided and classified.Resulting neural networks can then be used for handwriting character recognition, allowing the platform to reconstruct each word in the handwritten text. This technology can be particularly useful in situations where people need to quickly share information, but don't have access to a computer or other electronic device. By converting handwritten notes into editable text, this platform makes it easier to read, edit, and share information, regardless of the format in which it was originally written.