{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:QUO3ME4CJDHU7JBO7UNYYNOMZI","short_pith_number":"pith:QUO3ME4C","schema_version":"1.0","canonical_sha256":"851db6138248cf4fa42efd1b8c35ccca377c8343c6613151af179edbe725b8d2","source":{"kind":"arxiv","id":"2605.26095","version":1},"attestation_state":"computed","paper":{"title":"Pixel-Level Pavement Distress Assessment Using Instance Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bibesh Pyakurel (University of Wisconsin - Green Bay), Kong Pheng Yang (University of Wisconsin - Green Bay), Logan Dewick (University of Wisconsin - Green Bay), M. G. Sarwar Murshed (University of Wisconsin - Green Bay), Nazim Choudhury (University of Wisconsin - Green Bay)","submitted_at":"2026-05-25T17:53:23Z","abstract_excerpt":"Automated pavement distress assessment requires more than image-level classification or coarse bounding box detection, demanding precise localization of thin, branching, and irregular cracks to achieve the geometric precision necessary for maintenance-relevant quantification. This paper presents a vision-based pavement distress analysis system based on Mask R-CNN instance segmentation and evaluates it on UWGB-StreetCrack, a custom field-collected roadway image dataset acquired with a vehicle-mounted smartphone and manually annotated with polygon labels for longitudinal cracks, transverse crack"},"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":"2605.26095","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-25T17:53:23Z","cross_cats_sorted":[],"title_canon_sha256":"9904e3baeb3b0f033ccd901cbf9b73ce0bafc496348a689999a59fc4e9077753","abstract_canon_sha256":"9f4d1f7d7f308fe5f8033ac15459fd6fc001de49d26c59b97807fb4df4e65301"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T02:05:27.222015Z","signature_b64":"Wuo4Y5jeZftTo9rIV1Bn61Eym6/FnhXe9XrJLBuVLxICrPdmqkExGroaYo0RG3LyXEnmSEWdUJHbfrJzRK1qDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"851db6138248cf4fa42efd1b8c35ccca377c8343c6613151af179edbe725b8d2","last_reissued_at":"2026-05-26T02:05:27.221176Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T02:05:27.221176Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Pixel-Level Pavement Distress Assessment Using Instance Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bibesh Pyakurel (University of Wisconsin - Green Bay), Kong Pheng Yang (University of Wisconsin - Green Bay), Logan Dewick (University of Wisconsin - Green Bay), M. G. Sarwar Murshed (University of Wisconsin - Green Bay), Nazim Choudhury (University of Wisconsin - Green Bay)","submitted_at":"2026-05-25T17:53:23Z","abstract_excerpt":"Automated pavement distress assessment requires more than image-level classification or coarse bounding box detection, demanding precise localization of thin, branching, and irregular cracks to achieve the geometric precision necessary for maintenance-relevant quantification. This paper presents a vision-based pavement distress analysis system based on Mask R-CNN instance segmentation and evaluates it on UWGB-StreetCrack, a custom field-collected roadway image dataset acquired with a vehicle-mounted smartphone and manually annotated with polygon labels for longitudinal cracks, transverse crack"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.26095","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/2605.26095/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":"2605.26095","created_at":"2026-05-26T02:05:27.221332+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.26095v1","created_at":"2026-05-26T02:05:27.221332+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.26095","created_at":"2026-05-26T02:05:27.221332+00:00"},{"alias_kind":"pith_short_12","alias_value":"QUO3ME4CJDHU","created_at":"2026-05-26T02:05:27.221332+00:00"},{"alias_kind":"pith_short_16","alias_value":"QUO3ME4CJDHU7JBO","created_at":"2026-05-26T02:05:27.221332+00:00"},{"alias_kind":"pith_short_8","alias_value":"QUO3ME4C","created_at":"2026-05-26T02:05:27.221332+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/QUO3ME4CJDHU7JBO7UNYYNOMZI","json":"https://pith.science/pith/QUO3ME4CJDHU7JBO7UNYYNOMZI.json","graph_json":"https://pith.science/api/pith-number/QUO3ME4CJDHU7JBO7UNYYNOMZI/graph.json","events_json":"https://pith.science/api/pith-number/QUO3ME4CJDHU7JBO7UNYYNOMZI/events.json","paper":"https://pith.science/paper/QUO3ME4C"},"agent_actions":{"view_html":"https://pith.science/pith/QUO3ME4CJDHU7JBO7UNYYNOMZI","download_json":"https://pith.science/pith/QUO3ME4CJDHU7JBO7UNYYNOMZI.json","view_paper":"https://pith.science/paper/QUO3ME4C","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.26095&json=true","fetch_graph":"https://pith.science/api/pith-number/QUO3ME4CJDHU7JBO7UNYYNOMZI/graph.json","fetch_events":"https://pith.science/api/pith-number/QUO3ME4CJDHU7JBO7UNYYNOMZI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QUO3ME4CJDHU7JBO7UNYYNOMZI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QUO3ME4CJDHU7JBO7UNYYNOMZI/action/storage_attestation","attest_author":"https://pith.science/pith/QUO3ME4CJDHU7JBO7UNYYNOMZI/action/author_attestation","sign_citation":"https://pith.science/pith/QUO3ME4CJDHU7JBO7UNYYNOMZI/action/citation_signature","submit_replication":"https://pith.science/pith/QUO3ME4CJDHU7JBO7UNYYNOMZI/action/replication_record"}},"created_at":"2026-05-26T02:05:27.221332+00:00","updated_at":"2026-05-26T02:05:27.221332+00:00"}