Evaluating structural pattern recognition for handwritten math via primitive label graphs

@inproceedings{Zanibbi2013EvaluatingSP,
  title={Evaluating structural pattern recognition for handwritten math via primitive label graphs},
  author={Richard Zanibbi and Harold Mouch{\`e}re and Christian Viard-Gaudin},
  booktitle={DRR},
  year={2013}
}
ABSTRACT Currently, structural pattern recognizer evaluations compare graphs of detected structure to target structures(i.e. ground truth) using recognition rates, recall and precision for object segmentation, classi cation andrelationships. In document recognition, these target objects (e.g. symbols) are frequently comprised of multipleprimitives (e.g. connected components, or strokes for online handwritten data), but current metrics do notcharacterize errors at the primitive level, from which… CONTINUE READING
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