Hackathon Challenge: Difference between revisions

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***This will allow some algorithms to exploit spatial information to identify elements. This format is, however, not a main focus for this hackathon.  
***This will allow some algorithms to exploit spatial information to identify elements. This format is, however, not a main focus for this hackathon.  
*Those wishing to pursue other goals such as image segmentation, finding specific elements, or improving usability & user interfaces to the OCR and parsing tools are encouraged to do so and report back to the group at the hackathon.
*Those wishing to pursue other goals such as image segmentation, finding specific elements, or improving usability & user interfaces to the OCR and parsing tools are encouraged to do so and report back to the group at the hackathon.
== Metrics and Evaluation ==
*CSV files generated by participants will be compared with CSV files created by humans.
*Metrics evaluation code will be in javascript or phython - Alex Thompson (iDigBio IT)...and can then be run by participants as desired in sequential attempts to improve the result.
**A Presence-Absence matrix
**Confusion Matrix
**F-Score (weighs correct / incorrect answers)
*Graphics may be created
**For example, with an F-score for each dwc element entry, we can generate a graph / histogram


Back to the [[2013 AOCR Hackathon Wiki| Hackathon Wiki]]
Back to the [[2013 AOCR Hackathon Wiki| Hackathon Wiki]]
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