{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:7HTJXVAIKBN7P6OMSN57W3BRS4","short_pith_number":"pith:7HTJXVAI","schema_version":"1.0","canonical_sha256":"f9e69bd408505bf7f9cc937bfb6c3197092ed1699c753e2f199bf66ac849153f","source":{"kind":"arxiv","id":"1201.5947","version":1},"attestation_state":"computed","paper":{"title":"Examplers based image fusion features for face recognition","license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Alex Pappachen James, Sima Dimitrijev","submitted_at":"2012-01-28T11:45:07Z","abstract_excerpt":"Examplers of a face are formed from multiple gallery images of a person and are used in the process of classification of a test image. We incorporate such examplers in forming a biologically inspired local binary decisions on similarity based face recognition method. As opposed to single model approaches such as face averages the exampler based approach results in higher recognition accu- racies and stability. Using multiple training samples per person, the method shows the following recognition accuracies: 99.0% on AR, 99.5% on FERET, 99.5% on ORL, 99.3% on EYALE, 100.0% on YALE and 100.0% on"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1201.5947","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","primary_cat":"cs.CV","submitted_at":"2012-01-28T11:45:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8e5844bd270ac7312a177f4a82a5f485472c27913e9abd88b8a93952a9f44591","abstract_canon_sha256":"8f621d42786bc6a5b5efbca741db829002eb6d3db073b5a582722d266757f96c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:03:34.192411Z","signature_b64":"LtpbMqq8WMoVeqg9WEAdk+8k6ZbLpV3cgK41w9ZtpP11EJ2fWut/P9sTM0SXw36C2t+Gtk0+CAQoJ8ovMk48Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f9e69bd408505bf7f9cc937bfb6c3197092ed1699c753e2f199bf66ac849153f","last_reissued_at":"2026-05-18T04:03:34.191690Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:03:34.191690Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Examplers based image fusion features for face recognition","license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Alex Pappachen James, Sima Dimitrijev","submitted_at":"2012-01-28T11:45:07Z","abstract_excerpt":"Examplers of a face are formed from multiple gallery images of a person and are used in the process of classification of a test image. We incorporate such examplers in forming a biologically inspired local binary decisions on similarity based face recognition method. As opposed to single model approaches such as face averages the exampler based approach results in higher recognition accu- racies and stability. Using multiple training samples per person, the method shows the following recognition accuracies: 99.0% on AR, 99.5% on FERET, 99.5% on ORL, 99.3% on EYALE, 100.0% on YALE and 100.0% on"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1201.5947","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1201.5947","created_at":"2026-05-18T04:03:34.191811+00:00"},{"alias_kind":"arxiv_version","alias_value":"1201.5947v1","created_at":"2026-05-18T04:03:34.191811+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1201.5947","created_at":"2026-05-18T04:03:34.191811+00:00"},{"alias_kind":"pith_short_12","alias_value":"7HTJXVAIKBN7","created_at":"2026-05-18T12:26:56.085431+00:00"},{"alias_kind":"pith_short_16","alias_value":"7HTJXVAIKBN7P6OM","created_at":"2026-05-18T12:26:56.085431+00:00"},{"alias_kind":"pith_short_8","alias_value":"7HTJXVAI","created_at":"2026-05-18T12:26:56.085431+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7HTJXVAIKBN7P6OMSN57W3BRS4","json":"https://pith.science/pith/7HTJXVAIKBN7P6OMSN57W3BRS4.json","graph_json":"https://pith.science/api/pith-number/7HTJXVAIKBN7P6OMSN57W3BRS4/graph.json","events_json":"https://pith.science/api/pith-number/7HTJXVAIKBN7P6OMSN57W3BRS4/events.json","paper":"https://pith.science/paper/7HTJXVAI"},"agent_actions":{"view_html":"https://pith.science/pith/7HTJXVAIKBN7P6OMSN57W3BRS4","download_json":"https://pith.science/pith/7HTJXVAIKBN7P6OMSN57W3BRS4.json","view_paper":"https://pith.science/paper/7HTJXVAI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1201.5947&json=true","fetch_graph":"https://pith.science/api/pith-number/7HTJXVAIKBN7P6OMSN57W3BRS4/graph.json","fetch_events":"https://pith.science/api/pith-number/7HTJXVAIKBN7P6OMSN57W3BRS4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7HTJXVAIKBN7P6OMSN57W3BRS4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7HTJXVAIKBN7P6OMSN57W3BRS4/action/storage_attestation","attest_author":"https://pith.science/pith/7HTJXVAIKBN7P6OMSN57W3BRS4/action/author_attestation","sign_citation":"https://pith.science/pith/7HTJXVAIKBN7P6OMSN57W3BRS4/action/citation_signature","submit_replication":"https://pith.science/pith/7HTJXVAIKBN7P6OMSN57W3BRS4/action/replication_record"}},"created_at":"2026-05-18T04:03:34.191811+00:00","updated_at":"2026-05-18T04:03:34.191811+00:00"}