Twin Convolutional Neural Networks to Classify Writers Using Handwriting Data
Date
2022
Authors
Lim, Andrew
Ommen, Danica
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Copyright 2022, The Authors
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Center for Statistics and Applications in Forensic Evidence
The Center for Statistics and Applications in Forensic Evidence (CSAFE) carries out research on the scientific foundations of forensic methods, develops novel statistical methods and transfers knowledge and technological innovations to the forensic science community. We collaborate with more than 80 researchers and across six universities to drive solutions to support our forensic community partners with accessible tools, open-source databases and educational opportunities.
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Statistics
As leaders in statistical research, collaboration, and education, the Department of Statistics at Iowa State University offers students an education like no other. We are committed to our mission of developing and applying statistical methods, and proud of our award-winning students and faculty.
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Center for Statistics and Applications in Forensic EvidenceStatistics
Abstract
Primary goals are to examine: 1. Write diversification versus representation. 2. Preservation of handwriting structure versus image density. 3. Input size versus training size. 4. Writer identification complexity assessment using various test sites.
Comments
The following poster was presented at the 106th International Association for Identification (IAI) Annual Educational Conference, Omaha, Nebraska, July 31-Aug 6, 2022. Posted with permission of CSAFE.