Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Ambiguity and constraint in mathematical expression recognition
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Recognizing Mathematical Expressions Using Tree Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy logic and probability applications: bridging the gap
Fuzzy logic and probability applications: bridging the gap
Mathematics recognition using graph rewriting
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1) - Volume 1
Mathematical Formula Recognition Using Virtual Link Network
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Recognition of On-line Handwritten Mathematical Formulas in the E-Chalk System
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
A global learning approach for an online handwritten mathematical expression recognition system
Pattern Recognition Letters
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Handwritten mathematical notation contains ambiguities of various kinds. Here we focus on ambiguity in spatial relationships; in particular, we use fuzzy logic to treat ambiguity in subscript-or-inline and inline-or-superscript spatial relationships. We extend an existing system for recognizing handwritten mathematical notation, adding the capability of producing a ranked list of interpretations rather than a single top-choice interpretation. Fuzzy membership values are assigned to each spatial relationship; a given pair of symbols can have non-zero membership in fuzzy sets subscript and inline, or in fuzzy sets inline and superscript. These fuzzy membership values are combined to produce an overall confidence value for the entire interpretation. We have modified the user interface of our system so that a user can quickly view and select from the ranked interpretations when the highest confidence interpretation is incorrect.