Research Areas
Biography and Research Information
OverviewAI-generated summary
Cindy Roullet's research focuses on the application of machine learning techniques to historical image collections. Her work investigates methods for extracting, classifying, and searching large datasets of historical images, alongside their associated textual captions. This approach aims to enhance the accessibility and usability of archival materials for researchers and the public. Roullet has contributed to scholarship with five publications, accumulating 17 citations and an h-index of 3. She collaborates with researchers at the University of Arkansas at Fayetteville, including David Fredrick, Rhodora G. Vennarucci, and John M. Gauch, with whom she shares co-authored publications. Her most recent publication was in 2021, indicating recent activity in her research area.
Metrics
- h-index: 3
- Publications: 5
- Citations: 17
Selected Publications
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Transfer Learning Methods for Extracting, Classifying and Searching Large Collections of Historical Images and Their Captions (2021)
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An Automated Technique to Recognize and Extract Images from Scanned Archaeological Documents (2019)
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SoC Design Of A Novel Cluster-Based Approach for Real-Time Lane Detection in Low Quality Images (2017)
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Vision-Based Path Construction and Maintenance for Indoor Guidance of Autonomous Ground Vehicles Based on Collaborative Smart Cameras (2016)
Collaboration Network
Top Collaborators
- Transfer Learning Methods for Extracting, Classifying and Searching Large Collections of Historical Images and Their Captions
- Transfer Learning Methods for Extracting, Classifying and Searching Large Collections of Historical Images and Their Captions
- Transfer Learning Methods for Extracting, Classifying and Searching Large Collections of Historical Images and Their Captions
- Transfer Learning Methods for Extracting, Classifying and Searching Large Collections of Historical Images and Their Captions
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