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For text-query-based keyword spotting from handwritten Chinese documents, the index is usually organized as a candidate lattice to overcome the ambiguity of character segmentation. Each edge in the lattice denotes a candidate character associated with a candidate class. Character similarity (between character and class) scores are calculated on each edge, and the similarity between a query word and...
This paper proposes a method for handwritten Chinese/Japanese text (character string) recognition based on semi-Markov conditional random fields (semi-CRFs). The high-order semi-CRF model is defined on a lattice containing all possible segmentation-recognition hypotheses of a string to elegantly fuse the scores of candidate character recognition and the compatibilities of geometric and linguistic...
The small form-factor of mobile handsets and the longer, variable latency of cellular networks are major hindrances to good user experience in mobile web related activities. Existing approaches have yet to adequately address the usability concerns caused by them. This paper describes the design and prototype implementation of MIntOS (Mobile Interaction Optimization System), a system for improving...
This paper describes a method of online handwritten Japanese text recognition by improved path evaluation. Based on a theoretical ground, the method evaluates the likelihood of candidate segmentation paths by combining scores of character pattern size, inner gap, character recognition, single and pair character position, candidate segmentation point and linguistic context, with the weight parameters...
This paper describes an online handwritten Japanese character string recognition system based on conditional random fields, which integrates the information of character recognition, linguistic context and geometric context in a principled framework, and can effectively overcome the variable length of candidate segmentation. For geometric context, we employ both unary and binary feature functions,...
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