CNN-BiLSTM model for English Handwriting Recognition: Comprehensive Evaluation on the IAM Dataset

no code implementations • 2 Jul 2023 • Firat Kizilirmak, Berrin Yanikoglu

Test time augmentation with rotation and shear transformations applied to the input image, is proposed to increase recognition of difficult cases and found to reduce the word error rate by 2. 5\% points.

Data Augmentation Handwriting Recognition