Flexible integrating recognition and semantic processing

Abstract

A method for character recognition and semantic for natural language processing comprising extracting a sequence of feature vectors from a sequence of input character images by a convolutional neural network (CNN) feature extractor. The sequence of feature vectors comprises a plurality of feature vectors, each feature vector representing an approximate-match of its corresponding input character in the sequence of input character images. The method further comprises applying a sequential classifier sequentially as a sliding window of a size of a plurality consecutive feature vectors upon the sequence of feature vectors from a first feature vector in the sequence of feature vectors to the last feature vector in the sequence of feature vectors; and recognizing an output character for a targeted feature vector among the applied-upon consecutive feature vectors within the sliding window as it is sliding across the sequence of feature vectors.

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