{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:AMQ4NANFPMI2GPGY7UWS2S4YTW","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":"2cd782772d901a53f048b1562ab5151dd2ab748b22290282e938bd945062711b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T11:18:01Z","title_canon_sha256":"e2fa9d707507dae7f5cbcb4aa8abb28d4f6c1da47cf6b517c9ef9da1da8b2167"},"schema_version":"1.0","source":{"id":"1907.09236","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.09236","created_at":"2026-05-17T23:39:59Z"},{"alias_kind":"arxiv_version","alias_value":"1907.09236v1","created_at":"2026-05-17T23:39:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.09236","created_at":"2026-05-17T23:39:59Z"},{"alias_kind":"pith_short_12","alias_value":"AMQ4NANFPMI2","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"AMQ4NANFPMI2GPGY","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"AMQ4NANF","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:6ddb3606032449e762f4ef8240995a722a12f8a7d64eec8b513fa55f13718daa","target":"graph","created_at":"2026-05-17T23:39:59Z","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":"Object detection from RGB images is a long-standing problem in image processing and computer vision. It has applications in various domains including robotics, surveillance, human-computer interaction, and medical diagnosis. With the availability of low cost 3D scanners, a large number of RGB-D object detection approaches have been proposed in the past years. This chapter provides a comprehensive survey of the recent developments in this field. We structure the chapter into two parts; the focus of the first part is on techniques that are based on hand-crafted features combined with machine lea","authors_text":"Hamid Laga, Isaac Ronald Ward, Mohammed Bennamoun","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T11:18:01Z","title":"RGB-D image-based Object Detection: from Traditional Methods to Deep Learning Techniques"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.09236","kind":"arxiv","version":1},"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:f3ce99b20a1e86e8108b9a05fd8d0cd48695ba97dcf438b86d525082b062b5c0","target":"record","created_at":"2026-05-17T23:39:59Z","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":"2cd782772d901a53f048b1562ab5151dd2ab748b22290282e938bd945062711b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-22T11:18:01Z","title_canon_sha256":"e2fa9d707507dae7f5cbcb4aa8abb28d4f6c1da47cf6b517c9ef9da1da8b2167"},"schema_version":"1.0","source":{"id":"1907.09236","kind":"arxiv","version":1}},"canonical_sha256":"0321c681a57b11a33cd8fd2d2d4b989d97826bfb7d9c434953922765b31e6586","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0321c681a57b11a33cd8fd2d2d4b989d97826bfb7d9c434953922765b31e6586","first_computed_at":"2026-05-17T23:39:59.763251Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:59.763251Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"K7RDt94f8HUuwJu89KhihtwgCYo9E5jKkyUqJ+g65S8lwAkXOlxdx/UqLURfeMVd7uj4+VwhzcwBj8aggzxAAg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:59.763704Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.09236","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f3ce99b20a1e86e8108b9a05fd8d0cd48695ba97dcf438b86d525082b062b5c0","sha256:6ddb3606032449e762f4ef8240995a722a12f8a7d64eec8b513fa55f13718daa"],"state_sha256":"2f43148ff652190d95a1e41ca6b9e0ebb0833565c948298d2451a5e465608f8b"}