{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:5KCS5G7LHH37MQQWAQ3C6L5TEC","short_pith_number":"pith:5KCS5G7L","schema_version":"1.0","canonical_sha256":"ea852e9beb39f7f6421604362f2fb3209d0a9558b4c5f44eec58d505c56794ec","source":{"kind":"arxiv","id":"1406.6854","version":1},"attestation_state":"computed","paper":{"title":"A Fully Automated Latent Fingerprint Matcher with Embedded Self-learning Segmentation Module","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.CR","authors_text":"Jiankun Hu, Jinwei Xu, Xiuping Jia","submitted_at":"2014-06-26T11:51:56Z","abstract_excerpt":"Latent fingerprint has the practical value to identify the suspects who have unintentionally left a trace of fingerprint in the crime scenes. However, designing a fully automated latent fingerprint matcher is a very challenging task as it needs to address many challenging issues including the separation of overlapping structured patterns over the partial and poor quality latent fingerprint image, and finding a match against a large background database that would have different resolutions. Currently there is no fully automated latent fingerprint matcher available to the public and most literat"},"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":"1406.6854","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2014-06-26T11:51:56Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"c4a885fb068e329e26323d1eeafac88d20f20739f69fe1b821e8bc03d62a925d","abstract_canon_sha256":"72300a11fbbd79792168a675b7b876aac9ec0611282f53acaef888641caefc3f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:48:55.660499Z","signature_b64":"3cgGC0rcv8nABLsRNF/fCkK2Ak/Z/gdDUZI6RsXpfHBD8pRHh0MaS5j2202Aelu77oyrDrsycYTgv39RVyRwAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ea852e9beb39f7f6421604362f2fb3209d0a9558b4c5f44eec58d505c56794ec","last_reissued_at":"2026-05-18T02:48:55.659894Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:48:55.659894Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Fully Automated Latent Fingerprint Matcher with Embedded Self-learning Segmentation Module","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.CR","authors_text":"Jiankun Hu, Jinwei Xu, Xiuping Jia","submitted_at":"2014-06-26T11:51:56Z","abstract_excerpt":"Latent fingerprint has the practical value to identify the suspects who have unintentionally left a trace of fingerprint in the crime scenes. However, designing a fully automated latent fingerprint matcher is a very challenging task as it needs to address many challenging issues including the separation of overlapping structured patterns over the partial and poor quality latent fingerprint image, and finding a match against a large background database that would have different resolutions. Currently there is no fully automated latent fingerprint matcher available to the public and most literat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.6854","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":"1406.6854","created_at":"2026-05-18T02:48:55.659981+00:00"},{"alias_kind":"arxiv_version","alias_value":"1406.6854v1","created_at":"2026-05-18T02:48:55.659981+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.6854","created_at":"2026-05-18T02:48:55.659981+00:00"},{"alias_kind":"pith_short_12","alias_value":"5KCS5G7LHH37","created_at":"2026-05-18T12:28:14.216126+00:00"},{"alias_kind":"pith_short_16","alias_value":"5KCS5G7LHH37MQQW","created_at":"2026-05-18T12:28:14.216126+00:00"},{"alias_kind":"pith_short_8","alias_value":"5KCS5G7L","created_at":"2026-05-18T12:28:14.216126+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/5KCS5G7LHH37MQQWAQ3C6L5TEC","json":"https://pith.science/pith/5KCS5G7LHH37MQQWAQ3C6L5TEC.json","graph_json":"https://pith.science/api/pith-number/5KCS5G7LHH37MQQWAQ3C6L5TEC/graph.json","events_json":"https://pith.science/api/pith-number/5KCS5G7LHH37MQQWAQ3C6L5TEC/events.json","paper":"https://pith.science/paper/5KCS5G7L"},"agent_actions":{"view_html":"https://pith.science/pith/5KCS5G7LHH37MQQWAQ3C6L5TEC","download_json":"https://pith.science/pith/5KCS5G7LHH37MQQWAQ3C6L5TEC.json","view_paper":"https://pith.science/paper/5KCS5G7L","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1406.6854&json=true","fetch_graph":"https://pith.science/api/pith-number/5KCS5G7LHH37MQQWAQ3C6L5TEC/graph.json","fetch_events":"https://pith.science/api/pith-number/5KCS5G7LHH37MQQWAQ3C6L5TEC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5KCS5G7LHH37MQQWAQ3C6L5TEC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5KCS5G7LHH37MQQWAQ3C6L5TEC/action/storage_attestation","attest_author":"https://pith.science/pith/5KCS5G7LHH37MQQWAQ3C6L5TEC/action/author_attestation","sign_citation":"https://pith.science/pith/5KCS5G7LHH37MQQWAQ3C6L5TEC/action/citation_signature","submit_replication":"https://pith.science/pith/5KCS5G7LHH37MQQWAQ3C6L5TEC/action/replication_record"}},"created_at":"2026-05-18T02:48:55.659981+00:00","updated_at":"2026-05-18T02:48:55.659981+00:00"}