{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:54FJUOFX4KSOF77MPKIGHD3XAX","short_pith_number":"pith:54FJUOFX","canonical_record":{"source":{"id":"2302.06093","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-02-13T04:25:05Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"76ee6355257047907e024dbbfac357c1c589eee32453c747b7d3c29a12e7a944","abstract_canon_sha256":"d42d42295477230df9ca64094c98757b08165ff37b7e5f3c54ad6461d5438688"},"schema_version":"1.0"},"canonical_sha256":"ef0a9a38b7e2a4e2ffec7a90638f7705c650bf267afc75231442c6a47f2a160b","source":{"kind":"arxiv","id":"2302.06093","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.06093","created_at":"2026-07-05T05:41:01Z"},{"alias_kind":"arxiv_version","alias_value":"2302.06093v1","created_at":"2026-07-05T05:41:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.06093","created_at":"2026-07-05T05:41:01Z"},{"alias_kind":"pith_short_12","alias_value":"54FJUOFX4KSO","created_at":"2026-07-05T05:41:01Z"},{"alias_kind":"pith_short_16","alias_value":"54FJUOFX4KSOF77M","created_at":"2026-07-05T05:41:01Z"},{"alias_kind":"pith_short_8","alias_value":"54FJUOFX","created_at":"2026-07-05T05:41:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:54FJUOFX4KSOF77MPKIGHD3XAX","target":"record","payload":{"canonical_record":{"source":{"id":"2302.06093","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-02-13T04:25:05Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"76ee6355257047907e024dbbfac357c1c589eee32453c747b7d3c29a12e7a944","abstract_canon_sha256":"d42d42295477230df9ca64094c98757b08165ff37b7e5f3c54ad6461d5438688"},"schema_version":"1.0"},"canonical_sha256":"ef0a9a38b7e2a4e2ffec7a90638f7705c650bf267afc75231442c6a47f2a160b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:41:01.917353Z","signature_b64":"Ql80bNdqDugcUPPsQ1XTHdu68O6l6efkUhpOIRuEQqpbrwWyHkIQrn6hVQC40VX6y9beW+Z7uSzzQj/dahdSDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ef0a9a38b7e2a4e2ffec7a90638f7705c650bf267afc75231442c6a47f2a160b","last_reissued_at":"2026-07-05T05:41:01.916891Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:41:01.916891Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.06093","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":"2026-07-05T05:41:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d+7orDdV/EeyuWbSQcNlURM0ex2mXXpxurV3UMB8qExex5bwXrdifPy1u8ty/OoNcmJcwLoUtmB1dVAcq/JsCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T00:16:51.569736Z"},"content_sha256":"6da1457bbe669efc6358134db016241faf0a1dcf60e758d1aaec8ce81cfae402","schema_version":"1.0","event_id":"sha256:6da1457bbe669efc6358134db016241faf0a1dcf60e758d1aaec8ce81cfae402"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:54FJUOFX4KSOF77MPKIGHD3XAX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning-Based Defect Recognitions for Autonomous UAV Inspections","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Kangcheng Liu","submitted_at":"2023-02-13T04:25:05Z","abstract_excerpt":"Automatic crack detection and segmentation play a significant role in the whole system of unmanned aerial vehicle inspections. In this paper, we have implemented a deep learning framework for crack detection based on classical network architectures including Alexnet, VGG, and Resnet. Moreover, inspired by the feature pyramid network architecture, a hierarchical convolutional neural network (CNN) deep learning framework which is efficient in crack segmentation is also proposed, and its performance of it is compared with other state-of-the-art network architecture. We have summarized the existin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.06093","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/2302.06093/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":"2026-07-05T05:41:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lkA5Gek7Exb0MagWKJNI3Y+WF3XbddJEGiB/Si4K28lHIxy2likOb/jFEIsjNOdRvfhK33xK9RUs9TS1IrUgDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T00:16:51.570113Z"},"content_sha256":"a474084710ede6ae136bbc9221f2a948d405ffed8fd92d85c40de389d31ef664","schema_version":"1.0","event_id":"sha256:a474084710ede6ae136bbc9221f2a948d405ffed8fd92d85c40de389d31ef664"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/54FJUOFX4KSOF77MPKIGHD3XAX/bundle.json","state_url":"https://pith.science/pith/54FJUOFX4KSOF77MPKIGHD3XAX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/54FJUOFX4KSOF77MPKIGHD3XAX/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":"2026-07-13T00:16:51Z","links":{"resolver":"https://pith.science/pith/54FJUOFX4KSOF77MPKIGHD3XAX","bundle":"https://pith.science/pith/54FJUOFX4KSOF77MPKIGHD3XAX/bundle.json","state":"https://pith.science/pith/54FJUOFX4KSOF77MPKIGHD3XAX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/54FJUOFX4KSOF77MPKIGHD3XAX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:54FJUOFX4KSOF77MPKIGHD3XAX","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":"d42d42295477230df9ca64094c98757b08165ff37b7e5f3c54ad6461d5438688","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-02-13T04:25:05Z","title_canon_sha256":"76ee6355257047907e024dbbfac357c1c589eee32453c747b7d3c29a12e7a944"},"schema_version":"1.0","source":{"id":"2302.06093","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.06093","created_at":"2026-07-05T05:41:01Z"},{"alias_kind":"arxiv_version","alias_value":"2302.06093v1","created_at":"2026-07-05T05:41:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.06093","created_at":"2026-07-05T05:41:01Z"},{"alias_kind":"pith_short_12","alias_value":"54FJUOFX4KSO","created_at":"2026-07-05T05:41:01Z"},{"alias_kind":"pith_short_16","alias_value":"54FJUOFX4KSOF77M","created_at":"2026-07-05T05:41:01Z"},{"alias_kind":"pith_short_8","alias_value":"54FJUOFX","created_at":"2026-07-05T05:41:01Z"}],"graph_snapshots":[{"event_id":"sha256:a474084710ede6ae136bbc9221f2a948d405ffed8fd92d85c40de389d31ef664","target":"graph","created_at":"2026-07-05T05:41:01Z","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/2302.06093/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automatic crack detection and segmentation play a significant role in the whole system of unmanned aerial vehicle inspections. In this paper, we have implemented a deep learning framework for crack detection based on classical network architectures including Alexnet, VGG, and Resnet. Moreover, inspired by the feature pyramid network architecture, a hierarchical convolutional neural network (CNN) deep learning framework which is efficient in crack segmentation is also proposed, and its performance of it is compared with other state-of-the-art network architecture. We have summarized the existin","authors_text":"Kangcheng Liu","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-02-13T04:25:05Z","title":"Learning-Based Defect Recognitions for Autonomous UAV Inspections"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.06093","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":"sha256:6da1457bbe669efc6358134db016241faf0a1dcf60e758d1aaec8ce81cfae402","target":"record","created_at":"2026-07-05T05:41:01Z","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":"d42d42295477230df9ca64094c98757b08165ff37b7e5f3c54ad6461d5438688","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-02-13T04:25:05Z","title_canon_sha256":"76ee6355257047907e024dbbfac357c1c589eee32453c747b7d3c29a12e7a944"},"schema_version":"1.0","source":{"id":"2302.06093","kind":"arxiv","version":1}},"canonical_sha256":"ef0a9a38b7e2a4e2ffec7a90638f7705c650bf267afc75231442c6a47f2a160b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ef0a9a38b7e2a4e2ffec7a90638f7705c650bf267afc75231442c6a47f2a160b","first_computed_at":"2026-07-05T05:41:01.916891Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:41:01.916891Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ql80bNdqDugcUPPsQ1XTHdu68O6l6efkUhpOIRuEQqpbrwWyHkIQrn6hVQC40VX6y9beW+Z7uSzzQj/dahdSDg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:41:01.917353Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.06093","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6da1457bbe669efc6358134db016241faf0a1dcf60e758d1aaec8ce81cfae402","sha256:a474084710ede6ae136bbc9221f2a948d405ffed8fd92d85c40de389d31ef664"],"state_sha256":"793411897d7b4f4a083cde039ebc48ae0cfa9a19c9fe019f57aa1ec36dd1432d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xyv2CXBspweQcSjq/9gwSRPUAMGgdfyiRvxTHYhtnx/OY0xvANQbgaWUJ2TYzxlOGYZ0NOo0WZW6jrT0n7zwDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-13T00:16:51.572540Z","bundle_sha256":"f569e9f7d3450306050530654ae537348fd936ef28bc23b396e52e5b896aa833"}}