Text-Independent Writer Identification via CNN Features and Joint Bayesian

@article{Tang2016TextIndependentWI,
  title={Text-Independent Writer Identification via CNN Features and Joint Bayesian},
  author={Youbao Tang and Xiangqian Wu},
  journal={2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR)},
  year={2016},
  pages={566-571}
}
This paper proposes a novel method for offline text-independent writer identification by using convolutional neural network (CNN) and joint Bayesian, which consists of two stages, i.e. feature extraction and writer identification. In the stage of feature extraction, since a large number of data is essential to train an effective CNN model with high generalizability and the amount of handwriting is limited in writer identification, a data augmentation technique is first developed to generate… CONTINUE READING

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