{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:2SJZBY42RGBTVD55RETEGC27PV","short_pith_number":"pith:2SJZBY42","schema_version":"1.0","canonical_sha256":"d49390e39a89833a8fbd8926430b5f7d69ad2cc0ff9762e69bd6575c55481674","source":{"kind":"arxiv","id":"1804.03320","version":1},"attestation_state":"computed","paper":{"title":"Automated Detection Methods for Solar Activities and an Application for Statistic Analysis of Solar Filament","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.SR","authors_text":"C. Fang, P. F. Chen, Q. Hao","submitted_at":"2018-04-10T03:00:36Z","abstract_excerpt":"With the rapid development of telescopes, both temporal cadence and the spatial resolution of observations are increasing. This in turn generates vast amount of data, which can be efficiently searched only with automated detections in order to derive the features of interest in the observations. A number of automated detection methods and algorithms have been developed for solar activities, based on the image processing and machine learning techniques. In this paper, after briefly reviewing some automated detection methods, we describe our efficient and versatile automated detection method for"},"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":"1804.03320","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.SR","submitted_at":"2018-04-10T03:00:36Z","cross_cats_sorted":[],"title_canon_sha256":"55214a809b201c2589164f3bd836c14c7c8a44def9f28c74b0f19df98edee877","abstract_canon_sha256":"5099e6b1655e91a755bde540643d0a043a650887df439969e11902df40ada24a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:55:14.821659Z","signature_b64":"JK2rK40WkZN1V0eXGD502jb3y4Uz5FtRIAS9GDzaxvv6j9yUyfdL6/Ywr3xwtNlQTZGst9bU0iqelAb2ZL1/BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d49390e39a89833a8fbd8926430b5f7d69ad2cc0ff9762e69bd6575c55481674","last_reissued_at":"2026-05-17T23:55:14.821216Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:55:14.821216Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Automated Detection Methods for Solar Activities and an Application for Statistic Analysis of Solar Filament","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.SR","authors_text":"C. Fang, P. F. Chen, Q. Hao","submitted_at":"2018-04-10T03:00:36Z","abstract_excerpt":"With the rapid development of telescopes, both temporal cadence and the spatial resolution of observations are increasing. This in turn generates vast amount of data, which can be efficiently searched only with automated detections in order to derive the features of interest in the observations. A number of automated detection methods and algorithms have been developed for solar activities, based on the image processing and machine learning techniques. In this paper, after briefly reviewing some automated detection methods, we describe our efficient and versatile automated detection method for"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.03320","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":"1804.03320","created_at":"2026-05-17T23:55:14.821277+00:00"},{"alias_kind":"arxiv_version","alias_value":"1804.03320v1","created_at":"2026-05-17T23:55:14.821277+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.03320","created_at":"2026-05-17T23:55:14.821277+00:00"},{"alias_kind":"pith_short_12","alias_value":"2SJZBY42RGBT","created_at":"2026-05-18T12:32:02.567920+00:00"},{"alias_kind":"pith_short_16","alias_value":"2SJZBY42RGBTVD55","created_at":"2026-05-18T12:32:02.567920+00:00"},{"alias_kind":"pith_short_8","alias_value":"2SJZBY42","created_at":"2026-05-18T12:32:02.567920+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/2SJZBY42RGBTVD55RETEGC27PV","json":"https://pith.science/pith/2SJZBY42RGBTVD55RETEGC27PV.json","graph_json":"https://pith.science/api/pith-number/2SJZBY42RGBTVD55RETEGC27PV/graph.json","events_json":"https://pith.science/api/pith-number/2SJZBY42RGBTVD55RETEGC27PV/events.json","paper":"https://pith.science/paper/2SJZBY42"},"agent_actions":{"view_html":"https://pith.science/pith/2SJZBY42RGBTVD55RETEGC27PV","download_json":"https://pith.science/pith/2SJZBY42RGBTVD55RETEGC27PV.json","view_paper":"https://pith.science/paper/2SJZBY42","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1804.03320&json=true","fetch_graph":"https://pith.science/api/pith-number/2SJZBY42RGBTVD55RETEGC27PV/graph.json","fetch_events":"https://pith.science/api/pith-number/2SJZBY42RGBTVD55RETEGC27PV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2SJZBY42RGBTVD55RETEGC27PV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2SJZBY42RGBTVD55RETEGC27PV/action/storage_attestation","attest_author":"https://pith.science/pith/2SJZBY42RGBTVD55RETEGC27PV/action/author_attestation","sign_citation":"https://pith.science/pith/2SJZBY42RGBTVD55RETEGC27PV/action/citation_signature","submit_replication":"https://pith.science/pith/2SJZBY42RGBTVD55RETEGC27PV/action/replication_record"}},"created_at":"2026-05-17T23:55:14.821277+00:00","updated_at":"2026-05-17T23:55:14.821277+00:00"}