{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:S5RDVUUPCR4WWFSREGJW3LZVJU","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":"1f6a0dc629e6564158dbadc0335e0f811c241fde5e65cb8cfaac9f1435eb2771","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-17T12:36:02Z","title_canon_sha256":"f268cb60001a309af666a870e866aa99df2879d0a9b345b0f211ad90346853b3"},"schema_version":"1.0","source":{"id":"1805.06725","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.06725","created_at":"2026-05-18T00:00:55Z"},{"alias_kind":"arxiv_version","alias_value":"1805.06725v3","created_at":"2026-05-18T00:00:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.06725","created_at":"2026-05-18T00:00:55Z"},{"alias_kind":"pith_short_12","alias_value":"S5RDVUUPCR4W","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"S5RDVUUPCR4WWFSR","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"S5RDVUUP","created_at":"2026-05-18T12:32:50Z"}],"graph_snapshots":[{"event_id":"sha256:6b4dcb106921ed429b7012de8e728ccb2685882418cce2784c58274a67a59ff3","target":"graph","created_at":"2026-05-18T00:00:55Z","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":"Anomaly detection is a classical problem in computer vision, namely the determination of the normal from the abnormal when datasets are highly biased towards one class (normal) due to the insufficient sample size of the other class (abnormal). While this can be addressed as a supervised learning problem, a significantly more challenging problem is that of detecting the unknown/unseen anomaly case that takes us instead into the space of a one-class, semi-supervised learning paradigm. We introduce such a novel anomaly detection model, by using a conditional generative adversarial network that jo","authors_text":"Amir Atapour-Abarghouei, Samet Akcay, Toby P. Breckon","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-17T12:36:02Z","title":"GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.06725","kind":"arxiv","version":3},"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":"sha256:4e2e47a1d32056494dcbc56ecb1af65b519a63d8f01ea0ad15bac32d162518b3","target":"record","created_at":"2026-05-18T00:00:55Z","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":"1f6a0dc629e6564158dbadc0335e0f811c241fde5e65cb8cfaac9f1435eb2771","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-17T12:36:02Z","title_canon_sha256":"f268cb60001a309af666a870e866aa99df2879d0a9b345b0f211ad90346853b3"},"schema_version":"1.0","source":{"id":"1805.06725","kind":"arxiv","version":3}},"canonical_sha256":"97623ad28f14796b165121936daf354d26e5cd2751ab3c4cc4da6b6900fff6b3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"97623ad28f14796b165121936daf354d26e5cd2751ab3c4cc4da6b6900fff6b3","first_computed_at":"2026-05-18T00:00:55.797397Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:00:55.797397Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qma/kEsWbxe5yK2nbVDCa6E3hVaJcE/RjjyYBjj9vSdWnCI0HO0fI90HwVPi45XXONdTJIQxwqftl9NsHdW4Cg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:00:55.797968Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.06725","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e2e47a1d32056494dcbc56ecb1af65b519a63d8f01ea0ad15bac32d162518b3","sha256:6b4dcb106921ed429b7012de8e728ccb2685882418cce2784c58274a67a59ff3"],"state_sha256":"1e95ad9ccae9390d2292751012d8b033ca914c818d6228b96e06c3cb4cdbb257"}