Advancements in Character Recognition Models

This chapter explores the complexities of a convolutional neural network (CNN) for character recognition in cursive writing, focusing on segmentation challenges and the integration of traditional computer vision techniques. It discusses the transition to a heuristic method for improved accuracy and the crucial role of contextual language models in resolving ambiguities. Additionally, the chapter outlines future plans for enhancing segmentation and recognition through innovative data collection methods and the use of generative models.