{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:E533AN6JCUBBETTVTHW425DBA2","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":"a2fb234506c1c5acab9bff09ac62de8504dbaecd5e53cfa77441d24468444703","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-04-21T17:54:37Z","title_canon_sha256":"4f80a82e8a0fba91da2fe47b0c9c4e12575a5106a38b1bf8c088324bb6ad65a5"},"schema_version":"1.0","source":{"id":"2204.10318","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2204.10318","created_at":"2026-07-05T04:16:48Z"},{"alias_kind":"arxiv_version","alias_value":"2204.10318v1","created_at":"2026-07-05T04:16:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.10318","created_at":"2026-07-05T04:16:48Z"},{"alias_kind":"pith_short_12","alias_value":"E533AN6JCUBB","created_at":"2026-07-05T04:16:48Z"},{"alias_kind":"pith_short_16","alias_value":"E533AN6JCUBBETTV","created_at":"2026-07-05T04:16:48Z"},{"alias_kind":"pith_short_8","alias_value":"E533AN6J","created_at":"2026-07-05T04:16:48Z"}],"graph_snapshots":[{"event_id":"sha256:bc7689718bca66f9891fb5403e1c524929eaa7b2a161b4adea02faa2ce877cbe","target":"graph","created_at":"2026-07-05T04:16:48Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2204.10318/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Anomaly detection is important for industrial automation and part quality assurance, and while humans can easily detect anomalies in components given a few examples, designing a generic automated system that can perform at human or above human capabilities remains a challenge. In this work, we present a simple new anomaly detection algorithm called FADS (feature-based anomaly detection system) which leverages pretrained convolutional neural networks (CNN) to generate a statistical model of nominal inputs by observing the activation of the convolutional filters. During inference the system comp","authors_text":"Anthony Garland, Kevin Potter, Matt Smith","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-04-21T17:54:37Z","title":"Feature anomaly detection system (FADS) for intelligent manufacturing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.10318","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":"sha256:423f6fe3143f3251960ffa6b612a1eebcf4bdaf95dddd35f6c31b8bbe0e486fa","target":"record","created_at":"2026-07-05T04:16:48Z","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":"a2fb234506c1c5acab9bff09ac62de8504dbaecd5e53cfa77441d24468444703","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-04-21T17:54:37Z","title_canon_sha256":"4f80a82e8a0fba91da2fe47b0c9c4e12575a5106a38b1bf8c088324bb6ad65a5"},"schema_version":"1.0","source":{"id":"2204.10318","kind":"arxiv","version":1}},"canonical_sha256":"2777b037c91502124e7599edcd746106afc75f1373b4d377fc6ceabe32c6273b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2777b037c91502124e7599edcd746106afc75f1373b4d377fc6ceabe32c6273b","first_computed_at":"2026-07-05T04:16:48.985526Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:16:48.985526Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wWAUUGQGXX6ds6qgURWPoMylR61cLtStO0298/ZSrZMaLRc5o2vYINdQKH96cOsy8yQo7VO/U4uJTAV38Co5Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:16:48.986112Z","signed_message":"canonical_sha256_bytes"},"source_id":"2204.10318","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:423f6fe3143f3251960ffa6b612a1eebcf4bdaf95dddd35f6c31b8bbe0e486fa","sha256:bc7689718bca66f9891fb5403e1c524929eaa7b2a161b4adea02faa2ce877cbe"],"state_sha256":"f635eafab33f4e9a0d283626697344b42d6f1a82ab1a7caa2e903fb39141e8bc"}