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Towards Unsupervised Learning for Handwriting Recognition.

, , , and . ICFHR, page 549-554. IEEE Computer Society, (2014)

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Improvement of Context Dependent Modeling for Arabic Handwriting Recognition., , and . ICFHR, page 494-499. IEEE Computer Society, (2014)On the Benefits of Convolutional Neural Network Combinations in Offline Handwriting Recognition., , and . ICFHR, page 193-198. IEEE Computer Society, (2016)Alignment models for recurrent neural networks.. RWTH Aachen University, Germany, (2020)Cross-entropy vs. squared error training: a theoretical and experimental comparison., , and . INTERSPEECH, page 1756-1760. ISCA, (2013)Comparison of Bernoulli and Gaussian HMMs Using a Vertical Repositioning Technique for Off-Line Handwriting Recognition., , , , , and . ICFHR, page 3-7. IEEE Computer Society, (2012)Bidirectional Decoder Networks for Attention-Based End-to-End Offline Handwriting Recognition., , and . ICFHR, page 361-366. IEEE Computer Society, (2016)Fast and Robust Training of Recurrent Neural Networks for Offline Handwriting Recognition., , and . ICFHR, page 279-284. IEEE Computer Society, (2014)Towards Unsupervised Learning for Handwriting Recognition., , , and . ICFHR, page 549-554. IEEE Computer Society, (2014)Handwriting Recognition with Large Multidimensional Long Short-Term Memory Recurrent Neural Networks., , and . ICFHR, page 228-233. IEEE Computer Society, (2016)Improvements in RWTH's System for Off-Line Handwriting Recognition., , and . ICDAR, page 935-939. IEEE Computer Society, (2013)