{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:4KBQOB5O6CZKDKY5NMZ2HTCW3I","short_pith_number":"pith:4KBQOB5O","schema_version":"1.0","canonical_sha256":"e2830707aef0b2a1ab1d6b33a3cc56da0a4fadd99f9e92e340d731a4db96a394","source":{"kind":"arxiv","id":"1810.02344","version":1},"attestation_state":"computed","paper":{"title":"Multi-view X-ray R-CNN","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Faraz Saeedan, Jan-Martin O. Steitz, Stefan Roth","submitted_at":"2018-10-04T17:48:54Z","abstract_excerpt":"Motivated by the detection of prohibited objects in carry-on luggage as a part of avionic security screening, we develop a CNN-based object detection approach for multi-view X-ray image data. Our contributions are two-fold. First, we introduce a novel multi-view pooling layer to perform a 3D aggregation of 2D CNN-features extracted from each view. To that end, our pooling layer exploits the known geometry of the imaging system to ensure geometric consistency of the feature aggregation. Second, we introduce an end-to-end trainable multi-view detection pipeline based on Faster R-CNN, which deriv"},"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":"1810.02344","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-10-04T17:48:54Z","cross_cats_sorted":[],"title_canon_sha256":"2d70b96e227310a63a4f184ba5e2d883f747620ae88203e8eb48bb9b0dafd850","abstract_canon_sha256":"d37d710f53dd9caa27537fa1df1626cea8c5d235e0bd1e7546c31fc8ab3249ba"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:05.584398Z","signature_b64":"MGau1VmT3WNhND9hNl9pDQKf7Qu2xOjnI6aUrMpnkbmFT6u8ibEiyNtuu5mB58nYdctT3ZiCfa6USiqsRCW0AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e2830707aef0b2a1ab1d6b33a3cc56da0a4fadd99f9e92e340d731a4db96a394","last_reissued_at":"2026-05-18T00:04:05.583705Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:05.583705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multi-view X-ray R-CNN","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Faraz Saeedan, Jan-Martin O. Steitz, Stefan Roth","submitted_at":"2018-10-04T17:48:54Z","abstract_excerpt":"Motivated by the detection of prohibited objects in carry-on luggage as a part of avionic security screening, we develop a CNN-based object detection approach for multi-view X-ray image data. Our contributions are two-fold. First, we introduce a novel multi-view pooling layer to perform a 3D aggregation of 2D CNN-features extracted from each view. To that end, our pooling layer exploits the known geometry of the imaging system to ensure geometric consistency of the feature aggregation. Second, we introduce an end-to-end trainable multi-view detection pipeline based on Faster R-CNN, which deriv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.02344","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":""},"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":"1810.02344","created_at":"2026-05-18T00:04:05.583808+00:00"},{"alias_kind":"arxiv_version","alias_value":"1810.02344v1","created_at":"2026-05-18T00:04:05.583808+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.02344","created_at":"2026-05-18T00:04:05.583808+00:00"},{"alias_kind":"pith_short_12","alias_value":"4KBQOB5O6CZK","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_16","alias_value":"4KBQOB5O6CZKDKY5","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_8","alias_value":"4KBQOB5O","created_at":"2026-05-18T12:32:05.422762+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/4KBQOB5O6CZKDKY5NMZ2HTCW3I","json":"https://pith.science/pith/4KBQOB5O6CZKDKY5NMZ2HTCW3I.json","graph_json":"https://pith.science/api/pith-number/4KBQOB5O6CZKDKY5NMZ2HTCW3I/graph.json","events_json":"https://pith.science/api/pith-number/4KBQOB5O6CZKDKY5NMZ2HTCW3I/events.json","paper":"https://pith.science/paper/4KBQOB5O"},"agent_actions":{"view_html":"https://pith.science/pith/4KBQOB5O6CZKDKY5NMZ2HTCW3I","download_json":"https://pith.science/pith/4KBQOB5O6CZKDKY5NMZ2HTCW3I.json","view_paper":"https://pith.science/paper/4KBQOB5O","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1810.02344&json=true","fetch_graph":"https://pith.science/api/pith-number/4KBQOB5O6CZKDKY5NMZ2HTCW3I/graph.json","fetch_events":"https://pith.science/api/pith-number/4KBQOB5O6CZKDKY5NMZ2HTCW3I/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4KBQOB5O6CZKDKY5NMZ2HTCW3I/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4KBQOB5O6CZKDKY5NMZ2HTCW3I/action/storage_attestation","attest_author":"https://pith.science/pith/4KBQOB5O6CZKDKY5NMZ2HTCW3I/action/author_attestation","sign_citation":"https://pith.science/pith/4KBQOB5O6CZKDKY5NMZ2HTCW3I/action/citation_signature","submit_replication":"https://pith.science/pith/4KBQOB5O6CZKDKY5NMZ2HTCW3I/action/replication_record"}},"created_at":"2026-05-18T00:04:05.583808+00:00","updated_at":"2026-05-18T00:04:05.583808+00:00"}