{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:5GMZ35WSXABILW4VVWM532KD67","short_pith_number":"pith:5GMZ35WS","canonical_record":{"source":{"id":"1907.09380","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T15:48:48Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8301c3d352c00e5908b2bd51fda594681b8d75c4c22c6628d116e428c682c14f","abstract_canon_sha256":"4f7bb7b55117b2e7fc4b0ec524b2c75eb18f9cd81d748ef9f1c1ecf7d826e37b"},"schema_version":"1.0"},"canonical_sha256":"e9999df6d2b80285db95ad99dde943f7e7ec54046e400d2c1a38b642e7df648f","source":{"kind":"arxiv","id":"1907.09380","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.09380","created_at":"2026-05-17T23:39:59Z"},{"alias_kind":"arxiv_version","alias_value":"1907.09380v1","created_at":"2026-05-17T23:39:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.09380","created_at":"2026-05-17T23:39:59Z"},{"alias_kind":"pith_short_12","alias_value":"5GMZ35WSXABI","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"5GMZ35WSXABILW4V","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"5GMZ35WS","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:5GMZ35WSXABILW4VVWM532KD67","target":"record","payload":{"canonical_record":{"source":{"id":"1907.09380","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T15:48:48Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"8301c3d352c00e5908b2bd51fda594681b8d75c4c22c6628d116e428c682c14f","abstract_canon_sha256":"4f7bb7b55117b2e7fc4b0ec524b2c75eb18f9cd81d748ef9f1c1ecf7d826e37b"},"schema_version":"1.0"},"canonical_sha256":"e9999df6d2b80285db95ad99dde943f7e7ec54046e400d2c1a38b642e7df648f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:39:59.363558Z","signature_b64":"sOtKHnu+JeeJPo+l1jRS+fbreTw2FEw20CNJ/2BDsomkUyNX7hsNn2BjX3mJfHJH8pX9EbgJCa75sNm/jFRWCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e9999df6d2b80285db95ad99dde943f7e7ec54046e400d2c1a38b642e7df648f","last_reissued_at":"2026-05-17T23:39:59.362993Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:39:59.362993Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.09380","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:39:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4/EoSACmfrqZJkfXMP1d0k5c6/xHUrTxVGrm0b4aGPssvTriVLr+yLFfroIqXjENuyHTnMR01bko3xwUzvU7Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T22:54:56.521345Z"},"content_sha256":"adacda8f07f47065253b4fff9633488d8bc82bb476ab5ab6cc022e34dfc49b73","schema_version":"1.0","event_id":"sha256:adacda8f07f47065253b4fff9633488d8bc82bb476ab5ab6cc022e34dfc49b73"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:5GMZ35WSXABILW4VVWM532KD67","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeepIris: Iris Recognition Using A Deep Learning Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"AmirAli Abdolrashidi, Shervin Minaee","submitted_at":"2019-07-22T15:48:48Z","abstract_excerpt":"Iris recognition has been an active research area during last few decades, because of its wide applications in security, from airports to homeland security border control. Different features and algorithms have been proposed for iris recognition in the past. In this paper, we propose an end-to-end deep learning framework for iris recognition based on residual convolutional neural network (CNN), which can jointly learn the feature representation and perform recognition. We train our model on a well-known iris recognition dataset using only a few training images from each class, and show promisi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.09380","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:39:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KFRzTwv+Nwz41t8skzwFrlda/pYnNmnU8bBokboL19aLR6yFIumoD37D5EwaJZv8KsgySPJlR6q5Z1i1TFIoCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T22:54:56.522013Z"},"content_sha256":"bc69009656bc4e954301a0b0b1e2d58a821a45227a8cc91fe95b1ef620f3f43f","schema_version":"1.0","event_id":"sha256:bc69009656bc4e954301a0b0b1e2d58a821a45227a8cc91fe95b1ef620f3f43f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5GMZ35WSXABILW4VVWM532KD67/bundle.json","state_url":"https://pith.science/pith/5GMZ35WSXABILW4VVWM532KD67/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5GMZ35WSXABILW4VVWM532KD67/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-25T22:54:56Z","links":{"resolver":"https://pith.science/pith/5GMZ35WSXABILW4VVWM532KD67","bundle":"https://pith.science/pith/5GMZ35WSXABILW4VVWM532KD67/bundle.json","state":"https://pith.science/pith/5GMZ35WSXABILW4VVWM532KD67/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5GMZ35WSXABILW4VVWM532KD67/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:5GMZ35WSXABILW4VVWM532KD67","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"4f7bb7b55117b2e7fc4b0ec524b2c75eb18f9cd81d748ef9f1c1ecf7d826e37b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T15:48:48Z","title_canon_sha256":"8301c3d352c00e5908b2bd51fda594681b8d75c4c22c6628d116e428c682c14f"},"schema_version":"1.0","source":{"id":"1907.09380","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.09380","created_at":"2026-05-17T23:39:59Z"},{"alias_kind":"arxiv_version","alias_value":"1907.09380v1","created_at":"2026-05-17T23:39:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.09380","created_at":"2026-05-17T23:39:59Z"},{"alias_kind":"pith_short_12","alias_value":"5GMZ35WSXABI","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"5GMZ35WSXABILW4V","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"5GMZ35WS","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:bc69009656bc4e954301a0b0b1e2d58a821a45227a8cc91fe95b1ef620f3f43f","target":"graph","created_at":"2026-05-17T23:39:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Iris recognition has been an active research area during last few decades, because of its wide applications in security, from airports to homeland security border control. Different features and algorithms have been proposed for iris recognition in the past. In this paper, we propose an end-to-end deep learning framework for iris recognition based on residual convolutional neural network (CNN), which can jointly learn the feature representation and perform recognition. We train our model on a well-known iris recognition dataset using only a few training images from each class, and show promisi","authors_text":"AmirAli Abdolrashidi, Shervin Minaee","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T15:48:48Z","title":"DeepIris: Iris Recognition Using A Deep Learning Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.09380","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:adacda8f07f47065253b4fff9633488d8bc82bb476ab5ab6cc022e34dfc49b73","target":"record","created_at":"2026-05-17T23:39:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"4f7bb7b55117b2e7fc4b0ec524b2c75eb18f9cd81d748ef9f1c1ecf7d826e37b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T15:48:48Z","title_canon_sha256":"8301c3d352c00e5908b2bd51fda594681b8d75c4c22c6628d116e428c682c14f"},"schema_version":"1.0","source":{"id":"1907.09380","kind":"arxiv","version":1}},"canonical_sha256":"e9999df6d2b80285db95ad99dde943f7e7ec54046e400d2c1a38b642e7df648f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e9999df6d2b80285db95ad99dde943f7e7ec54046e400d2c1a38b642e7df648f","first_computed_at":"2026-05-17T23:39:59.362993Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:59.362993Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sOtKHnu+JeeJPo+l1jRS+fbreTw2FEw20CNJ/2BDsomkUyNX7hsNn2BjX3mJfHJH8pX9EbgJCa75sNm/jFRWCA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:59.363558Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.09380","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:adacda8f07f47065253b4fff9633488d8bc82bb476ab5ab6cc022e34dfc49b73","sha256:bc69009656bc4e954301a0b0b1e2d58a821a45227a8cc91fe95b1ef620f3f43f"],"state_sha256":"10a3f04f9b658b0ff9d183f7f48ea9da6fffccd8502ac98cd35101dad8fcef22"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X1+Y5mXOesUFj/zCnhNa+T5bmkylYMIBbadi84WqovyV8JM44v2xbCJZyFH//QlLJLry6NGflQKVqc8tjjRTBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T22:54:56.525927Z","bundle_sha256":"ae9b1bfc74264a538aabb26aaee927fe48d293f91899e01e17a60a52e833487c"}}