{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:TPVXYWETUSTK556XYW2VGYJ6Q3","short_pith_number":"pith:TPVXYWET","schema_version":"1.0","canonical_sha256":"9beb7c5893a4a6aef7d7c5b553613e86d62deb03feccf2117dc09d9c0afdaf7e","source":{"kind":"arxiv","id":"2404.01842","version":1},"attestation_state":"computed","paper":{"title":"Semi-Supervised Domain Adaptation for Wildfire Detection","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Geonu Lee, Jisu Kim, Jooyoung Jang, Minkook Cho, Nojun Kwak, Soohyung Lee, Young Hwang, Youngseo Cha","submitted_at":"2024-04-02T11:03:13Z","abstract_excerpt":"Recently, both the frequency and intensity of wildfires have increased worldwide, primarily due to climate change. In this paper, we propose a novel protocol for wildfire detection, leveraging semi-supervised Domain Adaptation for object detection, accompanied by a corresponding dataset designed for use by both academics and industries. Our dataset encompasses 30 times more diverse labeled scenes for the current largest benchmark wildfire dataset, HPWREN, and introduces a new labeling policy for wildfire detection. Inspired by CoordConv, we propose a robust baseline, Location-Aware Object Dete"},"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":"2404.01842","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-04-02T11:03:13Z","cross_cats_sorted":[],"title_canon_sha256":"a430ed62daec9c4e179494494fe949372946cc2f3aeb96e942b3369d08f780fe","abstract_canon_sha256":"4349fc254326b03d3cb1fc25677e9bc14ef0079649ec4eedc10d5739d6469e4a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:03:32.413850Z","signature_b64":"QHu02DRxsvlPRt+Gl9+1lh9CKJD/sWSi9+4x07VWpTpLMlKfsTG/Ws0e6TBuQ4+Ph+ZBpLkvX9NbZIEhAcgUCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9beb7c5893a4a6aef7d7c5b553613e86d62deb03feccf2117dc09d9c0afdaf7e","last_reissued_at":"2026-07-05T08:03:32.413428Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:03:32.413428Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Semi-Supervised Domain Adaptation for Wildfire Detection","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Geonu Lee, Jisu Kim, Jooyoung Jang, Minkook Cho, Nojun Kwak, Soohyung Lee, Young Hwang, Youngseo Cha","submitted_at":"2024-04-02T11:03:13Z","abstract_excerpt":"Recently, both the frequency and intensity of wildfires have increased worldwide, primarily due to climate change. In this paper, we propose a novel protocol for wildfire detection, leveraging semi-supervised Domain Adaptation for object detection, accompanied by a corresponding dataset designed for use by both academics and industries. Our dataset encompasses 30 times more diverse labeled scenes for the current largest benchmark wildfire dataset, HPWREN, and introduces a new labeling policy for wildfire detection. Inspired by CoordConv, we propose a robust baseline, Location-Aware Object Dete"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.01842","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/2404.01842/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":"2404.01842","created_at":"2026-07-05T08:03:32.413486+00:00"},{"alias_kind":"arxiv_version","alias_value":"2404.01842v1","created_at":"2026-07-05T08:03:32.413486+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.01842","created_at":"2026-07-05T08:03:32.413486+00:00"},{"alias_kind":"pith_short_12","alias_value":"TPVXYWETUSTK","created_at":"2026-07-05T08:03:32.413486+00:00"},{"alias_kind":"pith_short_16","alias_value":"TPVXYWETUSTK556X","created_at":"2026-07-05T08:03:32.413486+00:00"},{"alias_kind":"pith_short_8","alias_value":"TPVXYWET","created_at":"2026-07-05T08:03:32.413486+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/TPVXYWETUSTK556XYW2VGYJ6Q3","json":"https://pith.science/pith/TPVXYWETUSTK556XYW2VGYJ6Q3.json","graph_json":"https://pith.science/api/pith-number/TPVXYWETUSTK556XYW2VGYJ6Q3/graph.json","events_json":"https://pith.science/api/pith-number/TPVXYWETUSTK556XYW2VGYJ6Q3/events.json","paper":"https://pith.science/paper/TPVXYWET"},"agent_actions":{"view_html":"https://pith.science/pith/TPVXYWETUSTK556XYW2VGYJ6Q3","download_json":"https://pith.science/pith/TPVXYWETUSTK556XYW2VGYJ6Q3.json","view_paper":"https://pith.science/paper/TPVXYWET","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2404.01842&json=true","fetch_graph":"https://pith.science/api/pith-number/TPVXYWETUSTK556XYW2VGYJ6Q3/graph.json","fetch_events":"https://pith.science/api/pith-number/TPVXYWETUSTK556XYW2VGYJ6Q3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TPVXYWETUSTK556XYW2VGYJ6Q3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TPVXYWETUSTK556XYW2VGYJ6Q3/action/storage_attestation","attest_author":"https://pith.science/pith/TPVXYWETUSTK556XYW2VGYJ6Q3/action/author_attestation","sign_citation":"https://pith.science/pith/TPVXYWETUSTK556XYW2VGYJ6Q3/action/citation_signature","submit_replication":"https://pith.science/pith/TPVXYWETUSTK556XYW2VGYJ6Q3/action/replication_record"}},"created_at":"2026-07-05T08:03:32.413486+00:00","updated_at":"2026-07-05T08:03:32.413486+00:00"}