{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:63LKA722MEWDWRZHRHOXGWF52B","short_pith_number":"pith:63LKA722","schema_version":"1.0","canonical_sha256":"f6d6a07f5a612c3b472789dd7358bdd04016585bd5962c37daece2f0a8dd57f7","source":{"kind":"arxiv","id":"1710.04943","version":1},"attestation_state":"computed","paper":{"title":"Object Classification in Images of Neoclassical Artifacts Using Deep Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bernhard Bermeitinger, Maria Christoforaki, Siegfried Handschuh, Simon Donig","submitted_at":"2017-10-13T14:35:27Z","abstract_excerpt":"In this paper, we report on our efforts for using Deep Learning for classifying artifacts and their features in digital visuals as a part of the Neoclassica framework. It was conceived to provide scholars with new methods for analyzing and classifying artifacts and aesthetic forms from the era of Classicism. The framework accommodates both traditional knowledge representation as a formal ontology and data-driven knowledge discovery, where cultural patterns will be identified by means of algorithms in statistical analysis and machine learning. We created a Deep Learning approach trained on phot"},"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":"1710.04943","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2017-10-13T14:35:27Z","cross_cats_sorted":[],"title_canon_sha256":"b75db17c91e7684d2b3fa5b51b948e3bd6523221a9ac4ed0b48662a0f9550244","abstract_canon_sha256":"f720a67077cb84f335d3d9697d3ffeb4b85d0aa16216eefb00da056777aca7f2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:32:56.255364Z","signature_b64":"h9BZwex7ZU7CK3dkdfJpjjcXCy0r4/viW6xL3zTqw7gVq2znmg65HZHITqpqDM4tGSgf1kXnXiIp+Afd//DfCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f6d6a07f5a612c3b472789dd7358bdd04016585bd5962c37daece2f0a8dd57f7","last_reissued_at":"2026-05-18T00:32:56.254670Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:32:56.254670Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Object Classification in Images of Neoclassical Artifacts Using Deep Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bernhard Bermeitinger, Maria Christoforaki, Siegfried Handschuh, Simon Donig","submitted_at":"2017-10-13T14:35:27Z","abstract_excerpt":"In this paper, we report on our efforts for using Deep Learning for classifying artifacts and their features in digital visuals as a part of the Neoclassica framework. It was conceived to provide scholars with new methods for analyzing and classifying artifacts and aesthetic forms from the era of Classicism. The framework accommodates both traditional knowledge representation as a formal ontology and data-driven knowledge discovery, where cultural patterns will be identified by means of algorithms in statistical analysis and machine learning. We created a Deep Learning approach trained on phot"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.04943","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":"1710.04943","created_at":"2026-05-18T00:32:56.254780+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.04943v1","created_at":"2026-05-18T00:32:56.254780+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.04943","created_at":"2026-05-18T00:32:56.254780+00:00"},{"alias_kind":"pith_short_12","alias_value":"63LKA722MEWD","created_at":"2026-05-18T12:31:03.183658+00:00"},{"alias_kind":"pith_short_16","alias_value":"63LKA722MEWDWRZH","created_at":"2026-05-18T12:31:03.183658+00:00"},{"alias_kind":"pith_short_8","alias_value":"63LKA722","created_at":"2026-05-18T12:31:03.183658+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/63LKA722MEWDWRZHRHOXGWF52B","json":"https://pith.science/pith/63LKA722MEWDWRZHRHOXGWF52B.json","graph_json":"https://pith.science/api/pith-number/63LKA722MEWDWRZHRHOXGWF52B/graph.json","events_json":"https://pith.science/api/pith-number/63LKA722MEWDWRZHRHOXGWF52B/events.json","paper":"https://pith.science/paper/63LKA722"},"agent_actions":{"view_html":"https://pith.science/pith/63LKA722MEWDWRZHRHOXGWF52B","download_json":"https://pith.science/pith/63LKA722MEWDWRZHRHOXGWF52B.json","view_paper":"https://pith.science/paper/63LKA722","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.04943&json=true","fetch_graph":"https://pith.science/api/pith-number/63LKA722MEWDWRZHRHOXGWF52B/graph.json","fetch_events":"https://pith.science/api/pith-number/63LKA722MEWDWRZHRHOXGWF52B/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/63LKA722MEWDWRZHRHOXGWF52B/action/timestamp_anchor","attest_storage":"https://pith.science/pith/63LKA722MEWDWRZHRHOXGWF52B/action/storage_attestation","attest_author":"https://pith.science/pith/63LKA722MEWDWRZHRHOXGWF52B/action/author_attestation","sign_citation":"https://pith.science/pith/63LKA722MEWDWRZHRHOXGWF52B/action/citation_signature","submit_replication":"https://pith.science/pith/63LKA722MEWDWRZHRHOXGWF52B/action/replication_record"}},"created_at":"2026-05-18T00:32:56.254780+00:00","updated_at":"2026-05-18T00:32:56.254780+00:00"}