{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:Y2KRYBIYHB7LONHNBEVM75BGQQ","short_pith_number":"pith:Y2KRYBIY","canonical_record":{"source":{"id":"2506.21135","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-26T10:32:37Z","cross_cats_sorted":[],"title_canon_sha256":"91f8db637e32a42a7b25704975ef15a2dee3bfee3d28acf10f66b0e0e3f8dcba","abstract_canon_sha256":"860be5d34ad30ba8f4ed94d15995fdb36724edbeae90c1a119e897fcfd12c4bd"},"schema_version":"1.0"},"canonical_sha256":"c6951c0518387eb734ed092acff4268423aa6a01dd1f8176841e10fca251890d","source":{"kind":"arxiv","id":"2506.21135","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.21135","created_at":"2026-07-05T11:27:40Z"},{"alias_kind":"arxiv_version","alias_value":"2506.21135v1","created_at":"2026-07-05T11:27:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21135","created_at":"2026-07-05T11:27:40Z"},{"alias_kind":"pith_short_12","alias_value":"Y2KRYBIYHB7L","created_at":"2026-07-05T11:27:40Z"},{"alias_kind":"pith_short_16","alias_value":"Y2KRYBIYHB7LONHN","created_at":"2026-07-05T11:27:40Z"},{"alias_kind":"pith_short_8","alias_value":"Y2KRYBIY","created_at":"2026-07-05T11:27:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:Y2KRYBIYHB7LONHNBEVM75BGQQ","target":"record","payload":{"canonical_record":{"source":{"id":"2506.21135","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-26T10:32:37Z","cross_cats_sorted":[],"title_canon_sha256":"91f8db637e32a42a7b25704975ef15a2dee3bfee3d28acf10f66b0e0e3f8dcba","abstract_canon_sha256":"860be5d34ad30ba8f4ed94d15995fdb36724edbeae90c1a119e897fcfd12c4bd"},"schema_version":"1.0"},"canonical_sha256":"c6951c0518387eb734ed092acff4268423aa6a01dd1f8176841e10fca251890d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:27:40.426839Z","signature_b64":"JcBFrokJtHH8G/e3dlhG7eOfwSfxZMPBR8Vi/xximTg85MtraTFaE1EKI1sygrOVYW7WaADjk7vcOKdEvX9IBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c6951c0518387eb734ed092acff4268423aa6a01dd1f8176841e10fca251890d","last_reissued_at":"2026-07-05T11:27:40.426377Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:27:40.426377Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.21135","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:27:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BNM7/JPp6UFQ/WKuTFlR43/kLC5zCyH9ByTELBzWYJ95TpHBYLFOTrrrjZlxGQac6pjm3xuy1p32KrL2K4zjCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:52:54.435475Z"},"content_sha256":"9f793b2529b71f6450ca15fd157651cf3b517b5d9ff9f79852f22e9db97610a4","schema_version":"1.0","event_id":"sha256:9f793b2529b71f6450ca15fd157651cf3b517b5d9ff9f79852f22e9db97610a4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:Y2KRYBIYHB7LONHNBEVM75BGQQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jiawei Hu","submitted_at":"2025-06-26T10:32:37Z","abstract_excerpt":"Surface defect detection in industrial scenarios is both crucial and technically demanding due to the wide variability in defect types, irregular shapes and sizes, fine-grained requirements, and complex material textures. Although recent advances in AI-based detectors have improved performance, existing methods often suffer from redundant features, limited detail sensitivity, and weak robustness under multiscale conditions. To address these challenges, we propose YOLO-FDA, a novel YOLO-based detection framework that integrates fine-grained detail enhancement and attention-guided feature fusion"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21135","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/2506.21135/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:27:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4m0cUVwf7dNCg6JBsyaG0btIDAGaA7WBGw7lqK9I4WyYDecwL5hBPGAig5HHFDDXZhyAbo1kB1SztJWR6dEOAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:52:54.435999Z"},"content_sha256":"8b4c7e888044a28637bdd30d0653d5a5d39be6143e63bd3d22fd16a36232c029","schema_version":"1.0","event_id":"sha256:8b4c7e888044a28637bdd30d0653d5a5d39be6143e63bd3d22fd16a36232c029"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y2KRYBIYHB7LONHNBEVM75BGQQ/bundle.json","state_url":"https://pith.science/pith/Y2KRYBIYHB7LONHNBEVM75BGQQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y2KRYBIYHB7LONHNBEVM75BGQQ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T15:52:54Z","links":{"resolver":"https://pith.science/pith/Y2KRYBIYHB7LONHNBEVM75BGQQ","bundle":"https://pith.science/pith/Y2KRYBIYHB7LONHNBEVM75BGQQ/bundle.json","state":"https://pith.science/pith/Y2KRYBIYHB7LONHNBEVM75BGQQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y2KRYBIYHB7LONHNBEVM75BGQQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:Y2KRYBIYHB7LONHNBEVM75BGQQ","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":"860be5d34ad30ba8f4ed94d15995fdb36724edbeae90c1a119e897fcfd12c4bd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-26T10:32:37Z","title_canon_sha256":"91f8db637e32a42a7b25704975ef15a2dee3bfee3d28acf10f66b0e0e3f8dcba"},"schema_version":"1.0","source":{"id":"2506.21135","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.21135","created_at":"2026-07-05T11:27:40Z"},{"alias_kind":"arxiv_version","alias_value":"2506.21135v1","created_at":"2026-07-05T11:27:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21135","created_at":"2026-07-05T11:27:40Z"},{"alias_kind":"pith_short_12","alias_value":"Y2KRYBIYHB7L","created_at":"2026-07-05T11:27:40Z"},{"alias_kind":"pith_short_16","alias_value":"Y2KRYBIYHB7LONHN","created_at":"2026-07-05T11:27:40Z"},{"alias_kind":"pith_short_8","alias_value":"Y2KRYBIY","created_at":"2026-07-05T11:27:40Z"}],"graph_snapshots":[{"event_id":"sha256:8b4c7e888044a28637bdd30d0653d5a5d39be6143e63bd3d22fd16a36232c029","target":"graph","created_at":"2026-07-05T11:27:40Z","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/2506.21135/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Surface defect detection in industrial scenarios is both crucial and technically demanding due to the wide variability in defect types, irregular shapes and sizes, fine-grained requirements, and complex material textures. Although recent advances in AI-based detectors have improved performance, existing methods often suffer from redundant features, limited detail sensitivity, and weak robustness under multiscale conditions. To address these challenges, we propose YOLO-FDA, a novel YOLO-based detection framework that integrates fine-grained detail enhancement and attention-guided feature fusion","authors_text":"Jiawei Hu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-26T10:32:37Z","title":"YOLO-FDA: Integrating Hierarchical Attention and Detail Enhancement for Surface Defect Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21135","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":"sha256:9f793b2529b71f6450ca15fd157651cf3b517b5d9ff9f79852f22e9db97610a4","target":"record","created_at":"2026-07-05T11:27:40Z","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":"860be5d34ad30ba8f4ed94d15995fdb36724edbeae90c1a119e897fcfd12c4bd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-06-26T10:32:37Z","title_canon_sha256":"91f8db637e32a42a7b25704975ef15a2dee3bfee3d28acf10f66b0e0e3f8dcba"},"schema_version":"1.0","source":{"id":"2506.21135","kind":"arxiv","version":1}},"canonical_sha256":"c6951c0518387eb734ed092acff4268423aa6a01dd1f8176841e10fca251890d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c6951c0518387eb734ed092acff4268423aa6a01dd1f8176841e10fca251890d","first_computed_at":"2026-07-05T11:27:40.426377Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:27:40.426377Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JcBFrokJtHH8G/e3dlhG7eOfwSfxZMPBR8Vi/xximTg85MtraTFaE1EKI1sygrOVYW7WaADjk7vcOKdEvX9IBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:27:40.426839Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.21135","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9f793b2529b71f6450ca15fd157651cf3b517b5d9ff9f79852f22e9db97610a4","sha256:8b4c7e888044a28637bdd30d0653d5a5d39be6143e63bd3d22fd16a36232c029"],"state_sha256":"2578efafebb783d478812ebe658f4792bfa26fccfd6327e00113046ec1f70775"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FFohBk2sud11ent6an/DZnLjlvBOlTfZ6UOkJYtpz7G6vSvgzrcD+3PCV1UIcE/HFqvSM4mpaeVf6O2P7m6VBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T15:52:54.440910Z","bundle_sha256":"a898a58747597dd7e86fec941204f8371f239c1a97498c1634d37f00ef1e02d5"}}