Stamp Classifier

Stamp classification research focuses on automatically extracting information from stamped images, aiming to improve efficiency in various applications. Current approaches leverage deep learning models, particularly Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), often incorporating techniques like Retrieval-Augmented Generation (RAG) for enhanced accuracy. These methods find application in diverse fields, including logistics (tracking parcel journeys), astronomy (classifying astronomical objects), and border control (analyzing visa stamps for travel pattern extraction), demonstrating the broad utility and impact of automated stamp analysis.