{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:NZR4GRAB3IUM2NAQOPFC6HJOBT","short_pith_number":"pith:NZR4GRAB","schema_version":"1.0","canonical_sha256":"6e63c34401da28cd341073ca2f1d2e0ccd83db0f537e74cc6f5a4629d275a881","source":{"kind":"arxiv","id":"2307.03425","version":1},"attestation_state":"computed","paper":{"title":"Registration-Free Hybrid Learning Empowers Simple Multimodal Imaging System for High-quality Fusion Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Haoran Dai, Shouyu Wang, Yinghan Guan, Yuanjie Gu, Zekuan Yu","submitted_at":"2023-07-07T07:11:37Z","abstract_excerpt":"Multimodal fusion detection always places high demands on the imaging system and image pre-processing, while either a high-quality pre-registration system or image registration processing is costly. Unfortunately, the existing fusion methods are designed for registered source images, and the fusion of inhomogeneous features, which denotes a pair of features at the same spatial location that expresses different semantic information, cannot achieve satisfactory performance via these methods. As a result, we propose IA-VFDnet, a CNN-Transformer hybrid learning framework with a unified high-qualit"},"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":"2307.03425","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-07-07T07:11:37Z","cross_cats_sorted":[],"title_canon_sha256":"2986f31005d4ee8a1d0e24440a228fb206fbf92ff2232ab266722f1f9dd5ef5b","abstract_canon_sha256":"0b53610e98222ae52c494396aab7d1af5909decbd331573d418b1c2832174dda"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:28:42.670150Z","signature_b64":"YzkBGNZ4vp7FgGIuViLoNv8hvC4vsvQpVhKRxZf5cp8gHTYCGw+4AQZuLdMtYZBK3+QfMaNbPD1dmoKgmvD3DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e63c34401da28cd341073ca2f1d2e0ccd83db0f537e74cc6f5a4629d275a881","last_reissued_at":"2026-07-05T06:28:42.669696Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:28:42.669696Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Registration-Free Hybrid Learning Empowers Simple Multimodal Imaging System for High-quality Fusion Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Haoran Dai, Shouyu Wang, Yinghan Guan, Yuanjie Gu, Zekuan Yu","submitted_at":"2023-07-07T07:11:37Z","abstract_excerpt":"Multimodal fusion detection always places high demands on the imaging system and image pre-processing, while either a high-quality pre-registration system or image registration processing is costly. Unfortunately, the existing fusion methods are designed for registered source images, and the fusion of inhomogeneous features, which denotes a pair of features at the same spatial location that expresses different semantic information, cannot achieve satisfactory performance via these methods. As a result, we propose IA-VFDnet, a CNN-Transformer hybrid learning framework with a unified high-qualit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.03425","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2307.03425/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":"2307.03425","created_at":"2026-07-05T06:28:42.669761+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.03425v1","created_at":"2026-07-05T06:28:42.669761+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.03425","created_at":"2026-07-05T06:28:42.669761+00:00"},{"alias_kind":"pith_short_12","alias_value":"NZR4GRAB3IUM","created_at":"2026-07-05T06:28:42.669761+00:00"},{"alias_kind":"pith_short_16","alias_value":"NZR4GRAB3IUM2NAQ","created_at":"2026-07-05T06:28:42.669761+00:00"},{"alias_kind":"pith_short_8","alias_value":"NZR4GRAB","created_at":"2026-07-05T06:28:42.669761+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/NZR4GRAB3IUM2NAQOPFC6HJOBT","json":"https://pith.science/pith/NZR4GRAB3IUM2NAQOPFC6HJOBT.json","graph_json":"https://pith.science/api/pith-number/NZR4GRAB3IUM2NAQOPFC6HJOBT/graph.json","events_json":"https://pith.science/api/pith-number/NZR4GRAB3IUM2NAQOPFC6HJOBT/events.json","paper":"https://pith.science/paper/NZR4GRAB"},"agent_actions":{"view_html":"https://pith.science/pith/NZR4GRAB3IUM2NAQOPFC6HJOBT","download_json":"https://pith.science/pith/NZR4GRAB3IUM2NAQOPFC6HJOBT.json","view_paper":"https://pith.science/paper/NZR4GRAB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.03425&json=true","fetch_graph":"https://pith.science/api/pith-number/NZR4GRAB3IUM2NAQOPFC6HJOBT/graph.json","fetch_events":"https://pith.science/api/pith-number/NZR4GRAB3IUM2NAQOPFC6HJOBT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NZR4GRAB3IUM2NAQOPFC6HJOBT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NZR4GRAB3IUM2NAQOPFC6HJOBT/action/storage_attestation","attest_author":"https://pith.science/pith/NZR4GRAB3IUM2NAQOPFC6HJOBT/action/author_attestation","sign_citation":"https://pith.science/pith/NZR4GRAB3IUM2NAQOPFC6HJOBT/action/citation_signature","submit_replication":"https://pith.science/pith/NZR4GRAB3IUM2NAQOPFC6HJOBT/action/replication_record"}},"created_at":"2026-07-05T06:28:42.669761+00:00","updated_at":"2026-07-05T06:28:42.669761+00:00"}