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- W2155126964 abstract "This work presents an unconstrained offline hand-written line recognition system based on hybrid HMM (Hidden Markov Model)/ANN (Artificial Neural Network) models. The particularity of the system lies in the use of an ensemble of connectionist/statistical character n-gram language models. These language models are trained with a text corpus at character level; therefore, no explicit lexicon is used during recognition. The recognizer is thus able to output words which do not belong to that corpus. The proposed system favorably behaves compared to using a standard character n-gram on the IAM database lines corpus and achieves error rates comparable to state-of-the-art lexicon-driven alternatives." @default.
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- W2155126964 date "2010-07-01" @default.
- W2155126964 modified "2023-10-03" @default.
- W2155126964 title "Unconstrained offline handwriting recognition using connectionist character N-grams" @default.
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- W2155126964 doi "https://doi.org/10.1109/ijcnn.2010.5596327" @default.
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