{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:IOMOWYDGTMNRD4HXFVL6QOCWO7","short_pith_number":"pith:IOMOWYDG","schema_version":"1.0","canonical_sha256":"4398eb60669b1b11f0f72d57e8385677cf419bd9238026450745088ecabde772","source":{"kind":"arxiv","id":"2006.11379","version":1},"attestation_state":"computed","paper":{"title":"Improving Train Track Safety using Drones, Computer Vision and Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anuraag Kaashyap, Kirthi Kumar","submitted_at":"2020-06-04T23:17:23Z","abstract_excerpt":"Millions of human casualties resulting from train accidents globally are caused by the inefficient, manual track inspections. Government agencies are seriously concerned about the safe operations of the rail industry after series of accidents reported across e USA and around the globe, mainly attributed to track defects. Casualties resulting from track defects result in billions of dollars loss in public and private investments and loss of revenue due to downtime, ultimately resulting in loss of the public's confidence. The manual, mundane, and expensive monitoring of rail track safety can be "},"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":"2006.11379","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-06-04T23:17:23Z","cross_cats_sorted":[],"title_canon_sha256":"ab0e9ce24ea32c113edd8ed000aca55546ed00d9633515ff3e8bcdd07f1a0faa","abstract_canon_sha256":"a2b51cd464b8154d1786480acc43770cf5fe1cb3ada37c0e02af30790ff3c30e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:11:49.687130Z","signature_b64":"NgTwv7llbFqUZDK8yGTrJJIA2CvRI2Q8ctK7tkZtUvQtN62PGc0jBYertCcuI5WMbyH3Zfb7Lrs8+IZgGLqbDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4398eb60669b1b11f0f72d57e8385677cf419bd9238026450745088ecabde772","last_reissued_at":"2026-07-05T01:11:49.686705Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:11:49.686705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Improving Train Track Safety using Drones, Computer Vision and Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anuraag Kaashyap, Kirthi Kumar","submitted_at":"2020-06-04T23:17:23Z","abstract_excerpt":"Millions of human casualties resulting from train accidents globally are caused by the inefficient, manual track inspections. Government agencies are seriously concerned about the safe operations of the rail industry after series of accidents reported across e USA and around the globe, mainly attributed to track defects. Casualties resulting from track defects result in billions of dollars loss in public and private investments and loss of revenue due to downtime, ultimately resulting in loss of the public's confidence. The manual, mundane, and expensive monitoring of rail track safety can be "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.11379","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2006.11379/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2006.11379","created_at":"2026-07-05T01:11:49.686763+00:00"},{"alias_kind":"arxiv_version","alias_value":"2006.11379v1","created_at":"2026-07-05T01:11:49.686763+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.11379","created_at":"2026-07-05T01:11:49.686763+00:00"},{"alias_kind":"pith_short_12","alias_value":"IOMOWYDGTMNR","created_at":"2026-07-05T01:11:49.686763+00:00"},{"alias_kind":"pith_short_16","alias_value":"IOMOWYDGTMNRD4HX","created_at":"2026-07-05T01:11:49.686763+00:00"},{"alias_kind":"pith_short_8","alias_value":"IOMOWYDG","created_at":"2026-07-05T01:11:49.686763+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/IOMOWYDGTMNRD4HXFVL6QOCWO7","json":"https://pith.science/pith/IOMOWYDGTMNRD4HXFVL6QOCWO7.json","graph_json":"https://pith.science/api/pith-number/IOMOWYDGTMNRD4HXFVL6QOCWO7/graph.json","events_json":"https://pith.science/api/pith-number/IOMOWYDGTMNRD4HXFVL6QOCWO7/events.json","paper":"https://pith.science/paper/IOMOWYDG"},"agent_actions":{"view_html":"https://pith.science/pith/IOMOWYDGTMNRD4HXFVL6QOCWO7","download_json":"https://pith.science/pith/IOMOWYDGTMNRD4HXFVL6QOCWO7.json","view_paper":"https://pith.science/paper/IOMOWYDG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2006.11379&json=true","fetch_graph":"https://pith.science/api/pith-number/IOMOWYDGTMNRD4HXFVL6QOCWO7/graph.json","fetch_events":"https://pith.science/api/pith-number/IOMOWYDGTMNRD4HXFVL6QOCWO7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IOMOWYDGTMNRD4HXFVL6QOCWO7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IOMOWYDGTMNRD4HXFVL6QOCWO7/action/storage_attestation","attest_author":"https://pith.science/pith/IOMOWYDGTMNRD4HXFVL6QOCWO7/action/author_attestation","sign_citation":"https://pith.science/pith/IOMOWYDGTMNRD4HXFVL6QOCWO7/action/citation_signature","submit_replication":"https://pith.science/pith/IOMOWYDGTMNRD4HXFVL6QOCWO7/action/replication_record"}},"created_at":"2026-07-05T01:11:49.686763+00:00","updated_at":"2026-07-05T01:11:49.686763+00:00"}