{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:7ZQ4NKFHCPUO666OLZQP2ON3DC","short_pith_number":"pith:7ZQ4NKFH","schema_version":"1.0","canonical_sha256":"fe61c6a8a713e8ef7bce5e60fd39bb1893d2ca372f2f96a4676133401207f6ab","source":{"kind":"arxiv","id":"1409.7474","version":1},"attestation_state":"computed","paper":{"title":"Extracting man-made objects from remote sensing images via fast level set evolutions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Qunming Wang, Wenzhong Shi, Zelang Miao, Zhongbin Li","submitted_at":"2014-09-26T06:17:23Z","abstract_excerpt":"Object extraction from remote sensing images has long been an intensive research topic in the field of surveying and mapping. Most existing methods are devoted to handling just one type of object and little attention has been paid to improving the computational efficiency. In recent years, level set evolution (LSE) has been shown to be very promising for object extraction in the community of image processing and computer vision because it can handle topological changes automatically while achieving high accuracy. However, the application of state-of-the-art LSEs is compromised by laborious par"},"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":"1409.7474","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-09-26T06:17:23Z","cross_cats_sorted":[],"title_canon_sha256":"87591d623ab8543a25bb7fc55818cfbe37e558b34841e284886d1c69bb00be9a","abstract_canon_sha256":"e53b8fc07a0ddc88ebd13d23dd64dc65d3ecfb280882c10969d94bdde84ebf85"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:29:05.123640Z","signature_b64":"VjQ3zVVV1UX2ptEHFnTBV7Jex1bDC6ZjVhPZ4qH84gLRxAgxRG2s42JpTOjKjpkFlTap+30Q+O39Hk6qcoyNCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fe61c6a8a713e8ef7bce5e60fd39bb1893d2ca372f2f96a4676133401207f6ab","last_reissued_at":"2026-05-18T01:29:05.123059Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:29:05.123059Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Extracting man-made objects from remote sensing images via fast level set evolutions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Qunming Wang, Wenzhong Shi, Zelang Miao, Zhongbin Li","submitted_at":"2014-09-26T06:17:23Z","abstract_excerpt":"Object extraction from remote sensing images has long been an intensive research topic in the field of surveying and mapping. Most existing methods are devoted to handling just one type of object and little attention has been paid to improving the computational efficiency. In recent years, level set evolution (LSE) has been shown to be very promising for object extraction in the community of image processing and computer vision because it can handle topological changes automatically while achieving high accuracy. However, the application of state-of-the-art LSEs is compromised by laborious par"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1409.7474","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":""},"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":"1409.7474","created_at":"2026-05-18T01:29:05.123148+00:00"},{"alias_kind":"arxiv_version","alias_value":"1409.7474v1","created_at":"2026-05-18T01:29:05.123148+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1409.7474","created_at":"2026-05-18T01:29:05.123148+00:00"},{"alias_kind":"pith_short_12","alias_value":"7ZQ4NKFHCPUO","created_at":"2026-05-18T12:28:19.803747+00:00"},{"alias_kind":"pith_short_16","alias_value":"7ZQ4NKFHCPUO666O","created_at":"2026-05-18T12:28:19.803747+00:00"},{"alias_kind":"pith_short_8","alias_value":"7ZQ4NKFH","created_at":"2026-05-18T12:28:19.803747+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/7ZQ4NKFHCPUO666OLZQP2ON3DC","json":"https://pith.science/pith/7ZQ4NKFHCPUO666OLZQP2ON3DC.json","graph_json":"https://pith.science/api/pith-number/7ZQ4NKFHCPUO666OLZQP2ON3DC/graph.json","events_json":"https://pith.science/api/pith-number/7ZQ4NKFHCPUO666OLZQP2ON3DC/events.json","paper":"https://pith.science/paper/7ZQ4NKFH"},"agent_actions":{"view_html":"https://pith.science/pith/7ZQ4NKFHCPUO666OLZQP2ON3DC","download_json":"https://pith.science/pith/7ZQ4NKFHCPUO666OLZQP2ON3DC.json","view_paper":"https://pith.science/paper/7ZQ4NKFH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1409.7474&json=true","fetch_graph":"https://pith.science/api/pith-number/7ZQ4NKFHCPUO666OLZQP2ON3DC/graph.json","fetch_events":"https://pith.science/api/pith-number/7ZQ4NKFHCPUO666OLZQP2ON3DC/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7ZQ4NKFHCPUO666OLZQP2ON3DC/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7ZQ4NKFHCPUO666OLZQP2ON3DC/action/storage_attestation","attest_author":"https://pith.science/pith/7ZQ4NKFHCPUO666OLZQP2ON3DC/action/author_attestation","sign_citation":"https://pith.science/pith/7ZQ4NKFHCPUO666OLZQP2ON3DC/action/citation_signature","submit_replication":"https://pith.science/pith/7ZQ4NKFHCPUO666OLZQP2ON3DC/action/replication_record"}},"created_at":"2026-05-18T01:29:05.123148+00:00","updated_at":"2026-05-18T01:29:05.123148+00:00"}