{"id":{"repo_id":"unr","oai_identifier":"oai:scholarwolf.unr.edu:11714/11030"},"canonical_url":"https://search.dev.ndltd.org/etd/unr/oai:scholarwolf.unr.edu:11714/11030","repository":{"repo_id":"unr","name":"University of Nevada - Reno","base_url":"https://scholarwolf.unr.edu/server/oai/request"},"display":{"title":"Face Verification with Veridical and Caricatured Images using Prominent Attributes","abstract":"Caricatures, with their exaggerated features, offer a surprisingly efficient means for individuals to recognize each other compared to veridical (real) images. However, it is still a difficult task in machine learning to match veridical images to caricatures. This is due to the poor quality of caricature datasets, which often lack clear labels and contain low-quality images. Widely utilized veridical image datasets like CelebA also suffer from inadequate labeling. These label inconsistencies pose significant issues in accurate face verification tasks. Moreover, the effectiveness of neural networks has led to a shift in focus away from attribute-based representations, further complicating the matching process. In this thesis, we introduce a classification protocol for prominent facial feature recognition along with a verification protocol for matching celebrity veridical images to their caricatures. We utilize CarVer, a recently curated dataset comprising both veridical and caricature images accompanied by detailed prominent feature labels.","abstract_html":"Caricatures, with their exaggerated features, offer a surprisingly efficient means for individuals to recognize each other compared to veridical (real) images. However, it is still a difficult task in machine learning to match veridical images to caricatures. This is due to the poor quality of caricature datasets, which often lack clear labels and contain low-quality images. Widely utilized veridical image datasets like CelebA also suffer from inadequate labeling. These label inconsistencies pose significant issues in accurate face verification tasks. Moreover, the effectiveness of neural networks has led to a shift in focus away from attribute-based representations, further complicating the matching process. In this thesis, we introduce a classification protocol for prominent facial feature recognition along with a verification protocol for matching celebrity veridical images to their caricatures. We utilize CarVer, a recently curated dataset comprising both veridical and caricature images accompanied by detailed prominent feature labels.","abstract_has_math":false,"creators":["Sutariya, Jayam V."],"institution":"University of Nevada, Reno","degree_name":"Master of Science","degree_level":"Master's Degree","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Hand, Emily"],"committee_chairs":[],"committee_members":["Akter Anima, Bashira","Gumus, Mehmet"],"year":2024,"date_issued":"2024","date_published":"2024","updated_at":"2026-07-27T21:48:09Z","subjects":["Caricatures","Explainability","Face Verification","Facial Attributes","Feature Classification"],"languages":[],"rights":["Creative Commons Attribution-NonCommercial 4.0 International"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarwolf.unr.edu/handle/11714/11030","outbound_label":"Repository record","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Hand, Emily"]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Akter Anima, Bashira","Gumus, Mehmet"]},{"key":"dc:creator","label":"Author","values":["Sutariya, Jayam V."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2024-08-22T18:14:39Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2024-08-22T18:14:39Z"]},{"key":"dc:date.issued","label":"Date","values":["2024"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Master's Degree"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Nevada, Reno"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Caricatures","Explainability","Face Verification","Facial Attributes","Feature Classification"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Creative Commons Attribution-NonCommercial 4.0 International"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://scholarwolf.unr.edu/handle/11714/11030"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Caricatures, with their exaggerated features, offer a surprisingly efficient means for individuals to recognize each other compared to veridical (real) images. However, it is still a difficult task in machine learning to match veridical images to caricatures. This is due to the poor quality of caricature datasets, which often lack clear labels and contain low-quality images. Widely utilized veridical image datasets like CelebA also suffer from inadequate labeling. These label inconsistencies pose significant issues in accurate face verification tasks. Moreover, the effectiveness of neural networks has led to a shift in focus away from attribute-based representations, further complicating the matching process. In this thesis, we introduce a classification protocol for prominent facial feature recognition along with a verification protocol for matching celebrity veridical images to their caricatures. We utilize CarVer, a recently curated dataset comprising both veridical and caricature images accompanied by detailed prominent feature labels."]},{"key":"dc:format","label":"Dc Format","values":["PDF"]},{"key":"dc:title","label":"Title","values":["Face Verification with Veridical and Caricatured Images using Prominent Attributes"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hand, Emily"],"dc:contributor.committeemember":["Akter Anima, Bashira","Gumus, Mehmet"],"dc:creator":["Sutariya, Jayam V."],"dc:date.accessioned":["2024-08-22T18:14:39Z"],"dc:date.available":["2024-08-22T18:14:39Z"],"dc:date.issued":["2024"],"dc:description.abstract":["Caricatures, with their exaggerated features, offer a surprisingly efficient means for individuals to recognize each other compared to veridical (real) images. However, it is still a difficult task in machine learning to match veridical images to caricatures. This is due to the poor quality of caricature datasets, which often lack clear labels and contain low-quality images. Widely utilized veridical image datasets like CelebA also suffer from inadequate labeling. These label inconsistencies pose significant issues in accurate face verification tasks. Moreover, the effectiveness of neural networks has led to a shift in focus away from attribute-based representations, further complicating the matching process. In this thesis, we introduce a classification protocol for prominent facial feature recognition along with a verification protocol for matching celebrity veridical images to their caricatures. We utilize CarVer, a recently curated dataset comprising both veridical and caricature images accompanied by detailed prominent feature labels."],"dc:format":["PDF"],"dc:identifier.uri":["https://scholarwolf.unr.edu/handle/11714/11030"],"dc:rights":["Creative Commons Attribution-NonCommercial 4.0 International"],"dc:subject":["Caricatures","Explainability","Face Verification","Facial Attributes","Feature Classification"],"dc:title":["Face Verification with Veridical and Caricatured Images using Prominent Attributes"],"dc:type":["Thesis"],"thesis:degree_level":["Master's Degree"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["University of Nevada, Reno"]},"updated_at":"2026-07-27T21:48:09Z"}