Writer Identification

Writer identification, the task of determining an author from their handwriting, aims to leverage unique writing styles for authentication and forensic applications. Current research focuses on developing robust deep learning models, including convolutional neural networks (CNNs) often incorporating attention mechanisms, multi-scale feature fusion, and Siamese network architectures, to extract discriminative features from word-level or even single-character data. These advancements are improving accuracy, particularly in scenarios with limited data, and are being applied to diverse datasets including historical documents and online handwriting. The field's impact extends to areas like forensic science, document authentication, and data privacy through pseudonymization techniques.