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dc.creatorMiller, Eleanor K
dc.date.accessioned2018-05-23T15:36:34Z
dc.date.available2018-05-23T15:36:34Z
dc.date.created2018-05
dc.date.submittedMay 2018
dc.identifier.urihttp://hdl.handle.net/1969.1/166523
dc.description.abstractOrganic Chemistry is a challenging subject that requires dedicated practice to learn the meticulous rules composing the subject, otherwise a student risks failure. Current software to teach chemical structures contains drag-and-drop components and fails to provide students with true understanding of Organic Chemistry concepts. My solution is to integrate a sketch recognition interface that can learn to recognize components of various, user-sketched chemical structures with a back-propagation neural network that can be trained to translate the components of the chemical structure to determine correctness. The accuracy of the program will be rigorously tested to determine correctness in interpreting chemical structures.
dc.format.mimetypeapplication/pdf
dc.subjectChemistry
dc.subjectSketch Recognition
dc.subjectNeural Network
dc.subjectHand Drawn
dc.titleRecognizing Elementary Elements in Chemical Diagram Sketches
dc.typeThesis
thesis.degree.departmentComputer Science & Engineering
thesis.degree.disciplineComputer Science
thesis.degree.grantorUndergraduate Research Scholars Program
thesis.degree.nameBS
thesis.degree.levelUndergraduate
dc.contributor.committeeMemberHammond, Tracy
dc.type.materialtext
dc.date.updated2018-05-23T15:36:35Z


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