{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:QNYU2USZ6WU7CEZEPQP7CJVTOF","short_pith_number":"pith:QNYU2USZ","schema_version":"1.0","canonical_sha256":"83714d5259f5a9f113247c1ff126b37143d3a8157aadb8093ce443baca38fcda","source":{"kind":"arxiv","id":"2010.04421","version":1},"attestation_state":"computed","paper":{"title":"Long-distance tiny face detection based on enhanced YOLOv3 for unmanned system","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bo Zhou, Hong Qiao, Jia-Yi Chang, Ya-Jun Liu, Yan-Feng Lu","submitted_at":"2020-10-09T08:12:58Z","abstract_excerpt":"Remote tiny face detection applied in unmanned system is a challeng-ing work. The detector cannot obtain sufficient context semantic information due to the relatively long distance. The received poor fine-grained features make the face detection less accurate and robust. To solve the problem of long-distance detection of tiny faces, we propose an enhanced network model (YOLOv3-C) based on the YOLOv3 algorithm for unmanned platform. In this model, we bring in multi-scale features from feature pyramid networks and make the features fu-sion to adjust prediction feature map of the output, which im"},"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":"2010.04421","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-10-09T08:12:58Z","cross_cats_sorted":[],"title_canon_sha256":"c99e8e9071141e1dd4ea05ce69ec3f1c7e4a88033093900859ee3b113d0ee792","abstract_canon_sha256":"a447b9acf886a4c9d679ec97d67394f5475f93461be42a42f789582d7cef30e3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:41:37.208312Z","signature_b64":"jWjc/z6e3NNwWvZYZzl5vtH/eGYQpi7T7bWYVPDeAFwcewdWJ/378vazLfeSfes8QNBDA5PMHJliVMv07j/ZCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83714d5259f5a9f113247c1ff126b37143d3a8157aadb8093ce443baca38fcda","last_reissued_at":"2026-07-05T01:41:37.207863Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:41:37.207863Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Long-distance tiny face detection based on enhanced YOLOv3 for unmanned system","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bo Zhou, Hong Qiao, Jia-Yi Chang, Ya-Jun Liu, Yan-Feng Lu","submitted_at":"2020-10-09T08:12:58Z","abstract_excerpt":"Remote tiny face detection applied in unmanned system is a challeng-ing work. The detector cannot obtain sufficient context semantic information due to the relatively long distance. The received poor fine-grained features make the face detection less accurate and robust. To solve the problem of long-distance detection of tiny faces, we propose an enhanced network model (YOLOv3-C) based on the YOLOv3 algorithm for unmanned platform. In this model, we bring in multi-scale features from feature pyramid networks and make the features fu-sion to adjust prediction feature map of the output, which im"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.04421","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/2010.04421/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":"2010.04421","created_at":"2026-07-05T01:41:37.207935+00:00"},{"alias_kind":"arxiv_version","alias_value":"2010.04421v1","created_at":"2026-07-05T01:41:37.207935+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.04421","created_at":"2026-07-05T01:41:37.207935+00:00"},{"alias_kind":"pith_short_12","alias_value":"QNYU2USZ6WU7","created_at":"2026-07-05T01:41:37.207935+00:00"},{"alias_kind":"pith_short_16","alias_value":"QNYU2USZ6WU7CEZE","created_at":"2026-07-05T01:41:37.207935+00:00"},{"alias_kind":"pith_short_8","alias_value":"QNYU2USZ","created_at":"2026-07-05T01:41:37.207935+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/QNYU2USZ6WU7CEZEPQP7CJVTOF","json":"https://pith.science/pith/QNYU2USZ6WU7CEZEPQP7CJVTOF.json","graph_json":"https://pith.science/api/pith-number/QNYU2USZ6WU7CEZEPQP7CJVTOF/graph.json","events_json":"https://pith.science/api/pith-number/QNYU2USZ6WU7CEZEPQP7CJVTOF/events.json","paper":"https://pith.science/paper/QNYU2USZ"},"agent_actions":{"view_html":"https://pith.science/pith/QNYU2USZ6WU7CEZEPQP7CJVTOF","download_json":"https://pith.science/pith/QNYU2USZ6WU7CEZEPQP7CJVTOF.json","view_paper":"https://pith.science/paper/QNYU2USZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2010.04421&json=true","fetch_graph":"https://pith.science/api/pith-number/QNYU2USZ6WU7CEZEPQP7CJVTOF/graph.json","fetch_events":"https://pith.science/api/pith-number/QNYU2USZ6WU7CEZEPQP7CJVTOF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QNYU2USZ6WU7CEZEPQP7CJVTOF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QNYU2USZ6WU7CEZEPQP7CJVTOF/action/storage_attestation","attest_author":"https://pith.science/pith/QNYU2USZ6WU7CEZEPQP7CJVTOF/action/author_attestation","sign_citation":"https://pith.science/pith/QNYU2USZ6WU7CEZEPQP7CJVTOF/action/citation_signature","submit_replication":"https://pith.science/pith/QNYU2USZ6WU7CEZEPQP7CJVTOF/action/replication_record"}},"created_at":"2026-07-05T01:41:37.207935+00:00","updated_at":"2026-07-05T01:41:37.207935+00:00"}