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As rapid acquisition of large collections of fluorescence microscopy cell images can be automated, large-scale subcellular localizations of GFP-tagged fusion proteins can be practically accomplished. Semi-supervised learning has the potential of using a large set of unlabeled images for the recognition of subcellular organelle patterns, but the performance still has room for improvement. This paper...
In online handwritten math expression recognition, one-pass dynamic programming can produce high-quality symbol graphs in addition to best symbol sequence hypotheses, especially after discriminative training and trigram graph rescoring. Impact of symbol graphs on whole expression recognition, however, has not been referred to yet, since the interface of structure analysis module does not work well...
In the symbol recognition stage of online handwritten math expression recognition, the one-pass dynamic programming algorithm can produce high-quality symbol graphs in addition of the best recognized hypotheses. In this paper, we exploit the rich hypotheses embedded in a symbol graph to discriminatively train the exponential weights of different model likelihoods and the insertion penalty. The training...
A symbol decoding and graph generation algorithm for online handwritten mathematical expression recognition is formulated. It differs from our previous system and most other systems in two aspects: (1) it embeds stroke grouping into symbol identification to form a unified probabilistic framework for symbol recognition; and (2) a symbol graph rather than a list of symbol sequence hypotheses is generated,...
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