{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:ACCEBVP6GHOOISPNJVB662R2UW","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":"67dc471fe529547b7e1e10a64f8730e30abe7b6788ff0407d4c59f6871ea7094","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-05T12:39:30Z","title_canon_sha256":"b8817780717f595055b8e0b5fbdfaa5a65d28d1f5860d3b5c1b92c8740ac2fa1"},"schema_version":"1.0","source":{"id":"1709.01353","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1709.01353","created_at":"2026-05-17T23:48:57Z"},{"alias_kind":"arxiv_version","alias_value":"1709.01353v2","created_at":"2026-05-17T23:48:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.01353","created_at":"2026-05-17T23:48:57Z"},{"alias_kind":"pith_short_12","alias_value":"ACCEBVP6GHOO","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_16","alias_value":"ACCEBVP6GHOOISPN","created_at":"2026-05-18T12:31:05Z"},{"alias_kind":"pith_short_8","alias_value":"ACCEBVP6","created_at":"2026-05-18T12:31:05Z"}],"graph_snapshots":[{"event_id":"sha256:832aea0308782913e4fde7c92aaeeec421d592aed032e5562c7d75866f55e194","target":"graph","created_at":"2026-05-17T23:48:57Z","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":"Measuring visual similarity between two or more instances within a data distribution is a fundamental task in image retrieval. Theoretically, non-metric distances are able to generate a more complex and accurate similarity model than metric distances, provided that the non-linear data distribution is precisely captured by the system. In this work, we explore neural networks models for learning a non-metric similarity function for instance search. We argue that non-metric similarity functions based on neural networks can build a better model of human visual perception than standard metric dista","authors_text":"George Vogiatzis, Noa Garcia","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-05T12:39:30Z","title":"Learning Non-Metric Visual Similarity for Image Retrieval"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.01353","kind":"arxiv","version":2},"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:eb01242e3c42b2061be456a6135e2fb5f9747353336cb85fd3302cfbe76983c8","target":"record","created_at":"2026-05-17T23:48:57Z","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":"67dc471fe529547b7e1e10a64f8730e30abe7b6788ff0407d4c59f6871ea7094","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-05T12:39:30Z","title_canon_sha256":"b8817780717f595055b8e0b5fbdfaa5a65d28d1f5860d3b5c1b92c8740ac2fa1"},"schema_version":"1.0","source":{"id":"1709.01353","kind":"arxiv","version":2}},"canonical_sha256":"008440d5fe31dce449ed4d43ef6a3aa5abbbd899a325c706264443b1bf9f6ba3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"008440d5fe31dce449ed4d43ef6a3aa5abbbd899a325c706264443b1bf9f6ba3","first_computed_at":"2026-05-17T23:48:57.440499Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:57.440499Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"t1PILuRXRhqas0M53zcD5Z1QOnW1i9q6emHZszvmi2G0aPuh+Sfdbj8xqiyeBk6o8NzgklyVSSEeKdOiqTtfDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:57.441038Z","signed_message":"canonical_sha256_bytes"},"source_id":"1709.01353","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eb01242e3c42b2061be456a6135e2fb5f9747353336cb85fd3302cfbe76983c8","sha256:832aea0308782913e4fde7c92aaeeec421d592aed032e5562c7d75866f55e194"],"state_sha256":"f77b4c97c8f0cfaad362010e4d7043b072dfdc59196b84cfb0f0ce518f1e91e5"}