{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:32Z2ONQBAPF6ZWPAYQUUQ4XZXD","short_pith_number":"pith:32Z2ONQB","schema_version":"1.0","canonical_sha256":"deb3a7360103cbecd9e0c4294872f9b8de05c773bf3fb5ecb75a16331f067327","source":{"kind":"arxiv","id":"2412.11949","version":1},"attestation_state":"computed","paper":{"title":"Coconut Palm Tree Counting on Drone Images with Deep Object Detection and Synthetic Training Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Barbara B\\\"ohm, Claudia Linnhoff-Popien, Jonas Stein, Michael K\\\"olle, Robert M\\\"uller, Tobias Rohe","submitted_at":"2024-12-16T16:33:28Z","abstract_excerpt":"Drones have revolutionized various domains, including agriculture. Recent advances in deep learning have propelled among other things object detection in computer vision. This study utilized YOLO, a real-time object detector, to identify and count coconut palm trees in Ghanaian farm drone footage. The farm presented has lost track of its trees due to different planting phases. While manual counting would be very tedious and error-prone, accurately determining the number of trees is crucial for efficient planning and management of agricultural processes, especially for optimizing yields and pre"},"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":"2412.11949","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-16T16:33:28Z","cross_cats_sorted":[],"title_canon_sha256":"7e730828b89465a9f5ffd105bc66716c9f457906694538b639be3bcb44d10973","abstract_canon_sha256":"4653ab6f1f6c123245119e93c887260b7a81b1aab0689d1b4c24de0b755327e7"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:49:54.350811Z","signature_b64":"5lk1AYwMVOE9YQ/Gg5bib9niE6blJfJrZt0jyzRmFkrBKjukMFXKWp/Gf2vD/gnSFfHUXPomfEiQWJ+6J80zAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"deb3a7360103cbecd9e0c4294872f9b8de05c773bf3fb5ecb75a16331f067327","last_reissued_at":"2026-07-05T09:49:54.350311Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:49:54.350311Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Coconut Palm Tree Counting on Drone Images with Deep Object Detection and Synthetic Training Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Barbara B\\\"ohm, Claudia Linnhoff-Popien, Jonas Stein, Michael K\\\"olle, Robert M\\\"uller, Tobias Rohe","submitted_at":"2024-12-16T16:33:28Z","abstract_excerpt":"Drones have revolutionized various domains, including agriculture. Recent advances in deep learning have propelled among other things object detection in computer vision. This study utilized YOLO, a real-time object detector, to identify and count coconut palm trees in Ghanaian farm drone footage. The farm presented has lost track of its trees due to different planting phases. While manual counting would be very tedious and error-prone, accurately determining the number of trees is crucial for efficient planning and management of agricultural processes, especially for optimizing yields and pre"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.11949","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/2412.11949/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":"2412.11949","created_at":"2026-07-05T09:49:54.350381+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.11949v1","created_at":"2026-07-05T09:49:54.350381+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.11949","created_at":"2026-07-05T09:49:54.350381+00:00"},{"alias_kind":"pith_short_12","alias_value":"32Z2ONQBAPF6","created_at":"2026-07-05T09:49:54.350381+00:00"},{"alias_kind":"pith_short_16","alias_value":"32Z2ONQBAPF6ZWPA","created_at":"2026-07-05T09:49:54.350381+00:00"},{"alias_kind":"pith_short_8","alias_value":"32Z2ONQB","created_at":"2026-07-05T09:49:54.350381+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/32Z2ONQBAPF6ZWPAYQUUQ4XZXD","json":"https://pith.science/pith/32Z2ONQBAPF6ZWPAYQUUQ4XZXD.json","graph_json":"https://pith.science/api/pith-number/32Z2ONQBAPF6ZWPAYQUUQ4XZXD/graph.json","events_json":"https://pith.science/api/pith-number/32Z2ONQBAPF6ZWPAYQUUQ4XZXD/events.json","paper":"https://pith.science/paper/32Z2ONQB"},"agent_actions":{"view_html":"https://pith.science/pith/32Z2ONQBAPF6ZWPAYQUUQ4XZXD","download_json":"https://pith.science/pith/32Z2ONQBAPF6ZWPAYQUUQ4XZXD.json","view_paper":"https://pith.science/paper/32Z2ONQB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.11949&json=true","fetch_graph":"https://pith.science/api/pith-number/32Z2ONQBAPF6ZWPAYQUUQ4XZXD/graph.json","fetch_events":"https://pith.science/api/pith-number/32Z2ONQBAPF6ZWPAYQUUQ4XZXD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/32Z2ONQBAPF6ZWPAYQUUQ4XZXD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/32Z2ONQBAPF6ZWPAYQUUQ4XZXD/action/storage_attestation","attest_author":"https://pith.science/pith/32Z2ONQBAPF6ZWPAYQUUQ4XZXD/action/author_attestation","sign_citation":"https://pith.science/pith/32Z2ONQBAPF6ZWPAYQUUQ4XZXD/action/citation_signature","submit_replication":"https://pith.science/pith/32Z2ONQBAPF6ZWPAYQUUQ4XZXD/action/replication_record"}},"created_at":"2026-07-05T09:49:54.350381+00:00","updated_at":"2026-07-05T09:49:54.350381+00:00"}