{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:MHFULJZJNPXEC4QTOI5PN2WOOX","short_pith_number":"pith:MHFULJZJ","schema_version":"1.0","canonical_sha256":"61cb45a7296bee417213723af6eace75d22c9d18fb69fbb7e2ecf08bc3a4b24f","source":{"kind":"arxiv","id":"2507.12195","version":1},"attestation_state":"computed","paper":{"title":"Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Arkaprabha Basu","submitted_at":"2025-07-16T12:46:04Z","abstract_excerpt":"Modern digitised approaches have dramatically changed the preservation and restoration of cultural treasures, integrating computer scientists into multidisciplinary projects with ease. Machine learning, deep learning, and computer vision techniques have revolutionised developing sectors like 3D reconstruction, picture inpainting,IoT-based methods, genetic algorithms, and image processing with the integration of computer scientists into multidisciplinary initiatives. We suggest three cutting-edge techniques in recognition of the special qualities of Indian monuments, which are famous for their "},"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":"2507.12195","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-07-16T12:46:04Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f8e4582b077b02ba4b5ce51a213d4054d749282364f65a39fe0f97c1217180fd","abstract_canon_sha256":"07c5b62941a7d4169aa9211d5983b9ec7890aa4574f43d952c4b7610adef5210"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:38:16.192541Z","signature_b64":"yb8lNCngVI3C55AzejikUYu1Z5qK1fiPTKwsxKwD+DDPA+I1A4uve9eMXOroeGHEXHHlFwIkElJuft4G12zxDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"61cb45a7296bee417213723af6eace75d22c9d18fb69fbb7e2ecf08bc3a4b24f","last_reissued_at":"2026-07-05T11:38:16.191969Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:38:16.191969Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Revealing the Ancient Beauty: Digital Reconstruction of Temple Tiles using Computer Vision","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Arkaprabha Basu","submitted_at":"2025-07-16T12:46:04Z","abstract_excerpt":"Modern digitised approaches have dramatically changed the preservation and restoration of cultural treasures, integrating computer scientists into multidisciplinary projects with ease. Machine learning, deep learning, and computer vision techniques have revolutionised developing sectors like 3D reconstruction, picture inpainting,IoT-based methods, genetic algorithms, and image processing with the integration of computer scientists into multidisciplinary initiatives. We suggest three cutting-edge techniques in recognition of the special qualities of Indian monuments, which are famous for their "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.12195","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/2507.12195/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":"2507.12195","created_at":"2026-07-05T11:38:16.192047+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.12195v1","created_at":"2026-07-05T11:38:16.192047+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.12195","created_at":"2026-07-05T11:38:16.192047+00:00"},{"alias_kind":"pith_short_12","alias_value":"MHFULJZJNPXE","created_at":"2026-07-05T11:38:16.192047+00:00"},{"alias_kind":"pith_short_16","alias_value":"MHFULJZJNPXEC4QT","created_at":"2026-07-05T11:38:16.192047+00:00"},{"alias_kind":"pith_short_8","alias_value":"MHFULJZJ","created_at":"2026-07-05T11:38:16.192047+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/MHFULJZJNPXEC4QTOI5PN2WOOX","json":"https://pith.science/pith/MHFULJZJNPXEC4QTOI5PN2WOOX.json","graph_json":"https://pith.science/api/pith-number/MHFULJZJNPXEC4QTOI5PN2WOOX/graph.json","events_json":"https://pith.science/api/pith-number/MHFULJZJNPXEC4QTOI5PN2WOOX/events.json","paper":"https://pith.science/paper/MHFULJZJ"},"agent_actions":{"view_html":"https://pith.science/pith/MHFULJZJNPXEC4QTOI5PN2WOOX","download_json":"https://pith.science/pith/MHFULJZJNPXEC4QTOI5PN2WOOX.json","view_paper":"https://pith.science/paper/MHFULJZJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.12195&json=true","fetch_graph":"https://pith.science/api/pith-number/MHFULJZJNPXEC4QTOI5PN2WOOX/graph.json","fetch_events":"https://pith.science/api/pith-number/MHFULJZJNPXEC4QTOI5PN2WOOX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MHFULJZJNPXEC4QTOI5PN2WOOX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MHFULJZJNPXEC4QTOI5PN2WOOX/action/storage_attestation","attest_author":"https://pith.science/pith/MHFULJZJNPXEC4QTOI5PN2WOOX/action/author_attestation","sign_citation":"https://pith.science/pith/MHFULJZJNPXEC4QTOI5PN2WOOX/action/citation_signature","submit_replication":"https://pith.science/pith/MHFULJZJNPXEC4QTOI5PN2WOOX/action/replication_record"}},"created_at":"2026-07-05T11:38:16.192047+00:00","updated_at":"2026-07-05T11:38:16.192047+00:00"}