Attention-Based End-to-End Network for Offline Writer Identification Using Word-Level Data

The authors propose an attention-based end-to-end convolutional neural network for offline writer identification using word-level data. The network combines writer-specific local features and writer-independent global features to generate a robust representation of writer characteristics.