{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:AFEZPV54UTZVW253B5VUCBGEXB","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"68a591cd18d7e2f261d332e01baa025455870b1a0178972a3ed464f361878493","cross_cats_sorted":["cs.AI","cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-17T09:51:12Z","title_canon_sha256":"982c2a79550c13c851ad39cc00cd9f2064f2266caf8c12e9b437a9b9b93b8d9f"},"schema_version":"1.0","source":{"id":"1904.08159","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.08159","created_at":"2026-05-17T23:45:19Z"},{"alias_kind":"arxiv_version","alias_value":"1904.08159v2","created_at":"2026-05-17T23:45:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.08159","created_at":"2026-05-17T23:45:19Z"},{"alias_kind":"pith_short_12","alias_value":"AFEZPV54UTZV","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"AFEZPV54UTZVW253","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"AFEZPV54","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:1b78611e3dfa0f118d6fb980e057c2cf2fca686970eb1e28bcb8c2102ee4e404","target":"graph","created_at":"2026-05-17T23:45:19Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"In this study, we present an analysis of model-based ensemble learning for 3D point-cloud object classification and detection. An ensemble of multiple model instances is known to outperform a single model instance, but there is little study of the topic of ensemble learning for 3D point clouds. First, an ensemble of multiple model instances trained on the same part of the $\\textit{ModelNet40}$ dataset was tested for seven deep learning, point cloud-based classification algorithms: $\\textit{PointNet}$, $\\textit{PointNet++}$, $\\textit{SO-Net}$, $\\textit{KCNet}$, $\\textit{DeepSets}$, $\\textit{DGC","authors_text":"Daniel Koguciuk, {\\L}ukasz Chechli\\'nski, Tarek El-Gaaly","cross_cats":["cs.AI","cs.LG","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-17T09:51:12Z","title":"3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.08159","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:93ca8878fa41caa3010ec41042abb45f8740549b9394b51ac861ff1ca15d8945","target":"record","created_at":"2026-05-17T23:45:19Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"68a591cd18d7e2f261d332e01baa025455870b1a0178972a3ed464f361878493","cross_cats_sorted":["cs.AI","cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-17T09:51:12Z","title_canon_sha256":"982c2a79550c13c851ad39cc00cd9f2064f2266caf8c12e9b437a9b9b93b8d9f"},"schema_version":"1.0","source":{"id":"1904.08159","kind":"arxiv","version":2}},"canonical_sha256":"014997d7bca4f35b6bbb0f6b4104c4b84ff143355d89784d1f4728ce5d1e16a0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"014997d7bca4f35b6bbb0f6b4104c4b84ff143355d89784d1f4728ce5d1e16a0","first_computed_at":"2026-05-17T23:45:19.918768Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:45:19.918768Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/WshaB3yAdLiscQIHadurREYpZl+/RUysOB1aj+nwv1IR4Vqw45rfsk9RV2CEqR1xXAS3szpIl9jZ5Lx2XJkDA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:45:19.919400Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.08159","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:93ca8878fa41caa3010ec41042abb45f8740549b9394b51ac861ff1ca15d8945","sha256:1b78611e3dfa0f118d6fb980e057c2cf2fca686970eb1e28bcb8c2102ee4e404"],"state_sha256":"5bd6e75887371e9ba986437373ca5ac9aad92f2324b332fcc63fd24cf2676fbc"}