{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7GU3IFR5TLP2ZG2DT352W26ME7","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":"a731b8df9fcd81b9fabb6f7286eab033e01041081507fd6056ef2391dd98a0b4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-05-06T12:24:49Z","title_canon_sha256":"87002ace5872447734daa932b76afe305dd682718180b5d8cb2d52dd406e8d64"},"schema_version":"1.0","source":{"id":"2405.03413","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.03413","created_at":"2026-07-05T08:27:07Z"},{"alias_kind":"arxiv_version","alias_value":"2405.03413v3","created_at":"2026-07-05T08:27:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.03413","created_at":"2026-07-05T08:27:07Z"},{"alias_kind":"pith_short_12","alias_value":"7GU3IFR5TLP2","created_at":"2026-07-05T08:27:07Z"},{"alias_kind":"pith_short_16","alias_value":"7GU3IFR5TLP2ZG2D","created_at":"2026-07-05T08:27:07Z"},{"alias_kind":"pith_short_8","alias_value":"7GU3IFR5","created_at":"2026-07-05T08:27:07Z"}],"graph_snapshots":[{"event_id":"sha256:950a3ca2b0b828e6d4e8ebdff939529456298c8618c79ad91a4ae805b70de7b6","target":"graph","created_at":"2026-07-05T08:27:07Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2405.03413/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper explores how deep learning techniques can improve visual-based SLAM performance in challenging environments. By combining deep feature extraction and deep matching methods, we introduce a versatile hybrid visual SLAM system designed to enhance adaptability in challenging scenarios, such as low-light conditions, dynamic lighting, weak-texture areas, and severe jitter. Our system supports multiple modes, including monocular, stereo, monocular-inertial, and stereo-inertial configurations. We also perform analysis how to combine visual SLAM with deep learning methods to enlighten other ","authors_text":"Shuaixin Li, Zhang Xiao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-05-06T12:24:49Z","title":"A real-time, robust and versatile visual-SLAM framework based on deep learning networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.03413","kind":"arxiv","version":3},"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":"sha256:11c9fe08bc456bcf050e519346cea0e219d7960476cb36b621c4669bad4d1634","target":"record","created_at":"2026-07-05T08:27:07Z","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":"a731b8df9fcd81b9fabb6f7286eab033e01041081507fd6056ef2391dd98a0b4","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-05-06T12:24:49Z","title_canon_sha256":"87002ace5872447734daa932b76afe305dd682718180b5d8cb2d52dd406e8d64"},"schema_version":"1.0","source":{"id":"2405.03413","kind":"arxiv","version":3}},"canonical_sha256":"f9a9b4163d9adfac9b439efbab6bcc27c27187542001f923fa658d8d414c353d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f9a9b4163d9adfac9b439efbab6bcc27c27187542001f923fa658d8d414c353d","first_computed_at":"2026-07-05T08:27:07.897667Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:27:07.897667Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nYt1Ipsa2GyxXwhQrdLG+vTGmVRJqAVbgORdwWy4Un0GbzJmoIM3s8SuVIpeO2UtFqEHet7mdPyWIyMT6aJ4Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:27:07.898148Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.03413","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:11c9fe08bc456bcf050e519346cea0e219d7960476cb36b621c4669bad4d1634","sha256:950a3ca2b0b828e6d4e8ebdff939529456298c8618c79ad91a4ae805b70de7b6"],"state_sha256":"e30c27116272b523f69d40909b1a19e905a0a60922d9a3f3b28a4d5045ca9579"}