{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:4UT2IIUDBQUJNKPZRIUN634PD2","short_pith_number":"pith:4UT2IIUD","schema_version":"1.0","canonical_sha256":"e527a422830c2896a9f98a28df6f8f1e86133e8d8f7b5d6d4bcb9c5eed5b001b","source":{"kind":"arxiv","id":"2309.01279","version":1},"attestation_state":"computed","paper":{"title":"FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Grant Pearse, Luke Wallace, Maciej Wielgosz, Markus Hollaus, Peter Surov\\'y, Rasmus Astrup, Stefano Puliti","submitted_at":"2023-09-03T22:08:29Z","abstract_excerpt":"The FOR-instance dataset (available at https://doi.org/10.5281/zenodo.8287792) addresses the challenge of accurate individual tree segmentation from laser scanning data, crucial for understanding forest ecosystems and sustainable management. Despite the growing need for detailed tree data, automating segmentation and tracking scientific progress remains difficult. Existing methodologies often overfit small datasets and lack comparability, limiting their applicability. Amid the progress triggered by the emergence of deep learning methodologies, standardized benchmarking assumes paramount import"},"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":"2309.01279","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-09-03T22:08:29Z","cross_cats_sorted":[],"title_canon_sha256":"96eedb43eb0f436c1b26195b9762e861877a4f7e8fc2467e7b5a87079f03398e","abstract_canon_sha256":"1bad85a4503c27a700217d494e3ce078bef3dcf655b0afc39c6e2047de3c9201"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:47:35.601684Z","signature_b64":"zcuerLHWUfSIo9SRGbiI+KHjCmlTBzdSqRQVBjL4pZyqviLnvQnrGbWwo0bVoaR94MGRaH7YAxtFvzFFqqq7Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e527a422830c2896a9f98a28df6f8f1e86133e8d8f7b5d6d4bcb9c5eed5b001b","last_reissued_at":"2026-07-05T06:47:35.601252Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:47:35.601252Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Grant Pearse, Luke Wallace, Maciej Wielgosz, Markus Hollaus, Peter Surov\\'y, Rasmus Astrup, Stefano Puliti","submitted_at":"2023-09-03T22:08:29Z","abstract_excerpt":"The FOR-instance dataset (available at https://doi.org/10.5281/zenodo.8287792) addresses the challenge of accurate individual tree segmentation from laser scanning data, crucial for understanding forest ecosystems and sustainable management. Despite the growing need for detailed tree data, automating segmentation and tracking scientific progress remains difficult. Existing methodologies often overfit small datasets and lack comparability, limiting their applicability. Amid the progress triggered by the emergence of deep learning methodologies, standardized benchmarking assumes paramount import"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.01279","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/2309.01279/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":"2309.01279","created_at":"2026-07-05T06:47:35.601311+00:00"},{"alias_kind":"arxiv_version","alias_value":"2309.01279v1","created_at":"2026-07-05T06:47:35.601311+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.01279","created_at":"2026-07-05T06:47:35.601311+00:00"},{"alias_kind":"pith_short_12","alias_value":"4UT2IIUDBQUJ","created_at":"2026-07-05T06:47:35.601311+00:00"},{"alias_kind":"pith_short_16","alias_value":"4UT2IIUDBQUJNKPZ","created_at":"2026-07-05T06:47:35.601311+00:00"},{"alias_kind":"pith_short_8","alias_value":"4UT2IIUD","created_at":"2026-07-05T06:47:35.601311+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.19154","citing_title":"Viking Hill Dataset: A Lidar-Radar-Camera Dataset for Detection and Segmentation in Forest Scenes","ref_index":40,"is_internal_anchor":false},{"citing_arxiv_id":"2507.00170","citing_title":"SelvaBox: A high-resolution dataset for tropical tree crown detection","ref_index":65,"is_internal_anchor":false},{"citing_arxiv_id":"2604.13722","citing_title":"Granularity-Aware Transfer for Tree Instance Segmentation in Synthetic and Real Forests","ref_index":12,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/4UT2IIUDBQUJNKPZRIUN634PD2","json":"https://pith.science/pith/4UT2IIUDBQUJNKPZRIUN634PD2.json","graph_json":"https://pith.science/api/pith-number/4UT2IIUDBQUJNKPZRIUN634PD2/graph.json","events_json":"https://pith.science/api/pith-number/4UT2IIUDBQUJNKPZRIUN634PD2/events.json","paper":"https://pith.science/paper/4UT2IIUD"},"agent_actions":{"view_html":"https://pith.science/pith/4UT2IIUDBQUJNKPZRIUN634PD2","download_json":"https://pith.science/pith/4UT2IIUDBQUJNKPZRIUN634PD2.json","view_paper":"https://pith.science/paper/4UT2IIUD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2309.01279&json=true","fetch_graph":"https://pith.science/api/pith-number/4UT2IIUDBQUJNKPZRIUN634PD2/graph.json","fetch_events":"https://pith.science/api/pith-number/4UT2IIUDBQUJNKPZRIUN634PD2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4UT2IIUDBQUJNKPZRIUN634PD2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4UT2IIUDBQUJNKPZRIUN634PD2/action/storage_attestation","attest_author":"https://pith.science/pith/4UT2IIUDBQUJNKPZRIUN634PD2/action/author_attestation","sign_citation":"https://pith.science/pith/4UT2IIUDBQUJNKPZRIUN634PD2/action/citation_signature","submit_replication":"https://pith.science/pith/4UT2IIUDBQUJNKPZRIUN634PD2/action/replication_record"}},"created_at":"2026-07-05T06:47:35.601311+00:00","updated_at":"2026-07-05T06:47:35.601311+00:00"}