{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:7J5ND2AKAAANWG32L4URSVYFCJ","short_pith_number":"pith:7J5ND2AK","schema_version":"1.0","canonical_sha256":"fa7ad1e80a0000db1b7a5f29195705124120ab83df7da83ec3ba6af2b79a7122","source":{"kind":"arxiv","id":"2306.05671","version":3},"attestation_state":"computed","paper":{"title":"Topology-Aware Uncertainty for Image Segmentation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chao Chen, Prateek Prasanna, Saumya Gupta, Xiaoling Hu, Yikai Zhang","submitted_at":"2023-06-09T05:01:55Z","abstract_excerpt":"Segmentation of curvilinear structures such as vasculature and road networks is challenging due to relatively weak signals and complex geometry/topology. To facilitate and accelerate large scale annotation, one has to adopt semi-automatic approaches such as proofreading by experts. In this work, we focus on uncertainty estimation for such tasks, so that highly uncertain, and thus error-prone structures can be identified for human annotators to verify. Unlike most existing works, which provide pixel-wise uncertainty maps, we stipulate it is crucial to estimate uncertainty in the units of topolo"},"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":"2306.05671","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-06-09T05:01:55Z","cross_cats_sorted":[],"title_canon_sha256":"7f2c9f5fe423ab3003b30332a3d91f0418a789fc999959becc91e795b5d7c7e8","abstract_canon_sha256":"8fa5cfe8fcdaadc646b4ec4ba0071d421f296736e1e884f7d263faf4d5a4bf50"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:06:29.804309Z","signature_b64":"FbwkeS504a2jbCCBCSSm0siBiF/tF2HTWK4NTFh2NPGagiTRWzd307ZefzqeKRfrGhl23AFmfeB4ZAu7Cyj2DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fa7ad1e80a0000db1b7a5f29195705124120ab83df7da83ec3ba6af2b79a7122","last_reissued_at":"2026-07-05T07:06:29.803838Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:06:29.803838Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Topology-Aware Uncertainty for Image Segmentation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chao Chen, Prateek Prasanna, Saumya Gupta, Xiaoling Hu, Yikai Zhang","submitted_at":"2023-06-09T05:01:55Z","abstract_excerpt":"Segmentation of curvilinear structures such as vasculature and road networks is challenging due to relatively weak signals and complex geometry/topology. To facilitate and accelerate large scale annotation, one has to adopt semi-automatic approaches such as proofreading by experts. In this work, we focus on uncertainty estimation for such tasks, so that highly uncertain, and thus error-prone structures can be identified for human annotators to verify. Unlike most existing works, which provide pixel-wise uncertainty maps, we stipulate it is crucial to estimate uncertainty in the units of topolo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.05671","kind":"arxiv","version":3},"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/2306.05671/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":"2306.05671","created_at":"2026-07-05T07:06:29.803898+00:00"},{"alias_kind":"arxiv_version","alias_value":"2306.05671v3","created_at":"2026-07-05T07:06:29.803898+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.05671","created_at":"2026-07-05T07:06:29.803898+00:00"},{"alias_kind":"pith_short_12","alias_value":"7J5ND2AKAAAN","created_at":"2026-07-05T07:06:29.803898+00:00"},{"alias_kind":"pith_short_16","alias_value":"7J5ND2AKAAANWG32","created_at":"2026-07-05T07:06:29.803898+00:00"},{"alias_kind":"pith_short_8","alias_value":"7J5ND2AK","created_at":"2026-07-05T07:06:29.803898+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/7J5ND2AKAAANWG32L4URSVYFCJ","json":"https://pith.science/pith/7J5ND2AKAAANWG32L4URSVYFCJ.json","graph_json":"https://pith.science/api/pith-number/7J5ND2AKAAANWG32L4URSVYFCJ/graph.json","events_json":"https://pith.science/api/pith-number/7J5ND2AKAAANWG32L4URSVYFCJ/events.json","paper":"https://pith.science/paper/7J5ND2AK"},"agent_actions":{"view_html":"https://pith.science/pith/7J5ND2AKAAANWG32L4URSVYFCJ","download_json":"https://pith.science/pith/7J5ND2AKAAANWG32L4URSVYFCJ.json","view_paper":"https://pith.science/paper/7J5ND2AK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2306.05671&json=true","fetch_graph":"https://pith.science/api/pith-number/7J5ND2AKAAANWG32L4URSVYFCJ/graph.json","fetch_events":"https://pith.science/api/pith-number/7J5ND2AKAAANWG32L4URSVYFCJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7J5ND2AKAAANWG32L4URSVYFCJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7J5ND2AKAAANWG32L4URSVYFCJ/action/storage_attestation","attest_author":"https://pith.science/pith/7J5ND2AKAAANWG32L4URSVYFCJ/action/author_attestation","sign_citation":"https://pith.science/pith/7J5ND2AKAAANWG32L4URSVYFCJ/action/citation_signature","submit_replication":"https://pith.science/pith/7J5ND2AKAAANWG32L4URSVYFCJ/action/replication_record"}},"created_at":"2026-07-05T07:06:29.803898+00:00","updated_at":"2026-07-05T07:06:29.803898+00:00"}