{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:IZSJPLZZ5BBL52S3MOILVIKWUR","short_pith_number":"pith:IZSJPLZZ","schema_version":"1.0","canonical_sha256":"466497af39e842beea5b6390baa156a4777508b478c96cad3056e0ea40abe158","source":{"kind":"arxiv","id":"2203.01902","version":2},"attestation_state":"computed","paper":{"title":"Instance Segmentation for Autonomous Log Grasping in Forestry Operations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Fran\\c{c}ois Pomerleau, Jean-Michel Fortin, Olivier Gamache, Philippe Gigu\\`ere, Vincent Grondin","submitted_at":"2022-03-03T18:29:25Z","abstract_excerpt":"Wood logs picking is a challenging task to automate. Indeed, logs usually come in cluttered configurations, randomly orientated and overlapping. Recent work on log picking automation usually assume that the logs' pose is known, with little consideration given to the actual perception problem. In this paper, we squarely address the latter, using a data-driven approach. First, we introduce a novel dataset, named TimberSeg 1.0, that is densely annotated, i.e., that includes both bounding boxes and pixel-level mask annotations for logs. This dataset comprises 220 images with 2500 individually segm"},"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":"2203.01902","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-03T18:29:25Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"67f5d2dea34b3165f6c24fe03e3567cb33ac9b3be41832658fb03e54dc8a4ba2","abstract_canon_sha256":"08fabc63be169a7ec2092b466340c91e0f6635f98ca11b86caf4faf3a317a8b4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:08:03.582628Z","signature_b64":"kOqnYXS6uNTLUJdhv7MEYozJC4RXdXJSCQA/HpZNexjMW6GDojIHULfZ+9x0FPuplwFLCBmJy0XXM9OJ+JivCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"466497af39e842beea5b6390baa156a4777508b478c96cad3056e0ea40abe158","last_reissued_at":"2026-07-05T05:08:03.582180Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:08:03.582180Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Instance Segmentation for Autonomous Log Grasping in Forestry Operations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Fran\\c{c}ois Pomerleau, Jean-Michel Fortin, Olivier Gamache, Philippe Gigu\\`ere, Vincent Grondin","submitted_at":"2022-03-03T18:29:25Z","abstract_excerpt":"Wood logs picking is a challenging task to automate. Indeed, logs usually come in cluttered configurations, randomly orientated and overlapping. Recent work on log picking automation usually assume that the logs' pose is known, with little consideration given to the actual perception problem. In this paper, we squarely address the latter, using a data-driven approach. First, we introduce a novel dataset, named TimberSeg 1.0, that is densely annotated, i.e., that includes both bounding boxes and pixel-level mask annotations for logs. This dataset comprises 220 images with 2500 individually segm"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.01902","kind":"arxiv","version":2},"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/2203.01902/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":"2203.01902","created_at":"2026-07-05T05:08:03.582244+00:00"},{"alias_kind":"arxiv_version","alias_value":"2203.01902v2","created_at":"2026-07-05T05:08:03.582244+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.01902","created_at":"2026-07-05T05:08:03.582244+00:00"},{"alias_kind":"pith_short_12","alias_value":"IZSJPLZZ5BBL","created_at":"2026-07-05T05:08:03.582244+00:00"},{"alias_kind":"pith_short_16","alias_value":"IZSJPLZZ5BBL52S3","created_at":"2026-07-05T05:08:03.582244+00:00"},{"alias_kind":"pith_short_8","alias_value":"IZSJPLZZ","created_at":"2026-07-05T05:08:03.582244+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/IZSJPLZZ5BBL52S3MOILVIKWUR","json":"https://pith.science/pith/IZSJPLZZ5BBL52S3MOILVIKWUR.json","graph_json":"https://pith.science/api/pith-number/IZSJPLZZ5BBL52S3MOILVIKWUR/graph.json","events_json":"https://pith.science/api/pith-number/IZSJPLZZ5BBL52S3MOILVIKWUR/events.json","paper":"https://pith.science/paper/IZSJPLZZ"},"agent_actions":{"view_html":"https://pith.science/pith/IZSJPLZZ5BBL52S3MOILVIKWUR","download_json":"https://pith.science/pith/IZSJPLZZ5BBL52S3MOILVIKWUR.json","view_paper":"https://pith.science/paper/IZSJPLZZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2203.01902&json=true","fetch_graph":"https://pith.science/api/pith-number/IZSJPLZZ5BBL52S3MOILVIKWUR/graph.json","fetch_events":"https://pith.science/api/pith-number/IZSJPLZZ5BBL52S3MOILVIKWUR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IZSJPLZZ5BBL52S3MOILVIKWUR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IZSJPLZZ5BBL52S3MOILVIKWUR/action/storage_attestation","attest_author":"https://pith.science/pith/IZSJPLZZ5BBL52S3MOILVIKWUR/action/author_attestation","sign_citation":"https://pith.science/pith/IZSJPLZZ5BBL52S3MOILVIKWUR/action/citation_signature","submit_replication":"https://pith.science/pith/IZSJPLZZ5BBL52S3MOILVIKWUR/action/replication_record"}},"created_at":"2026-07-05T05:08:03.582244+00:00","updated_at":"2026-07-05T05:08:03.582244+00:00"}