{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:C6UZWZHBYACEYGNI53GLSNJP4W","short_pith_number":"pith:C6UZWZHB","schema_version":"1.0","canonical_sha256":"17a99b64e1c0044c19a8eeccb9352fe5a93080245fb4da74c38b71af2e5a4f70","source":{"kind":"arxiv","id":"1603.01068","version":2},"attestation_state":"computed","paper":{"title":"First Steps Toward Camera Model Identification with Convolutional Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CV","authors_text":"David G\\\"uera, Edward J. Delp, Luca Baroffio, Luca Bondi, Paolo Bestagini, Stefano Tubaro","submitted_at":"2016-03-03T12:10:47Z","abstract_excerpt":"Detecting the camera model used to shoot a picture enables to solve a wide series of forensic problems, from copyright infringement to ownership attribution. For this reason, the forensic community has developed a set of camera model identification algorithms that exploit characteristic traces left on acquired images by the processing pipelines specific of each camera model. In this paper, we investigate a novel approach to solve camera model identification problem. Specifically, we propose a data-driven algorithm based on convolutional neural networks, which learns features characterizing eac"},"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":"1603.01068","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-03-03T12:10:47Z","cross_cats_sorted":["cs.MM"],"title_canon_sha256":"4985e340b50b4cff6301611a404a7805053e7497892ce0b57dc73fce6cbc4fbd","abstract_canon_sha256":"aff25f277663530c4574a7bd663b136d299295115a056e2193ef7cfec39301b2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:33:23.931287Z","signature_b64":"LdU+n9CQge5Pv+EIpY+aP7PXktqWzq4vdK1MS6khGhdDXyANnqtytr/6futiKzdYRrvs0fTyn4VRM+gw46TrAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17a99b64e1c0044c19a8eeccb9352fe5a93080245fb4da74c38b71af2e5a4f70","last_reissued_at":"2026-05-18T00:33:23.930566Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:33:23.930566Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"First Steps Toward Camera Model Identification with Convolutional Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM"],"primary_cat":"cs.CV","authors_text":"David G\\\"uera, Edward J. Delp, Luca Baroffio, Luca Bondi, Paolo Bestagini, Stefano Tubaro","submitted_at":"2016-03-03T12:10:47Z","abstract_excerpt":"Detecting the camera model used to shoot a picture enables to solve a wide series of forensic problems, from copyright infringement to ownership attribution. For this reason, the forensic community has developed a set of camera model identification algorithms that exploit characteristic traces left on acquired images by the processing pipelines specific of each camera model. In this paper, we investigate a novel approach to solve camera model identification problem. Specifically, we propose a data-driven algorithm based on convolutional neural networks, which learns features characterizing eac"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1603.01068","kind":"arxiv","version":2},"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":"1603.01068","created_at":"2026-05-18T00:33:23.930684+00:00"},{"alias_kind":"arxiv_version","alias_value":"1603.01068v2","created_at":"2026-05-18T00:33:23.930684+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1603.01068","created_at":"2026-05-18T00:33:23.930684+00:00"},{"alias_kind":"pith_short_12","alias_value":"C6UZWZHBYACE","created_at":"2026-05-18T12:30:09.641336+00:00"},{"alias_kind":"pith_short_16","alias_value":"C6UZWZHBYACEYGNI","created_at":"2026-05-18T12:30:09.641336+00:00"},{"alias_kind":"pith_short_8","alias_value":"C6UZWZHB","created_at":"2026-05-18T12:30:09.641336+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/C6UZWZHBYACEYGNI53GLSNJP4W","json":"https://pith.science/pith/C6UZWZHBYACEYGNI53GLSNJP4W.json","graph_json":"https://pith.science/api/pith-number/C6UZWZHBYACEYGNI53GLSNJP4W/graph.json","events_json":"https://pith.science/api/pith-number/C6UZWZHBYACEYGNI53GLSNJP4W/events.json","paper":"https://pith.science/paper/C6UZWZHB"},"agent_actions":{"view_html":"https://pith.science/pith/C6UZWZHBYACEYGNI53GLSNJP4W","download_json":"https://pith.science/pith/C6UZWZHBYACEYGNI53GLSNJP4W.json","view_paper":"https://pith.science/paper/C6UZWZHB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1603.01068&json=true","fetch_graph":"https://pith.science/api/pith-number/C6UZWZHBYACEYGNI53GLSNJP4W/graph.json","fetch_events":"https://pith.science/api/pith-number/C6UZWZHBYACEYGNI53GLSNJP4W/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/C6UZWZHBYACEYGNI53GLSNJP4W/action/timestamp_anchor","attest_storage":"https://pith.science/pith/C6UZWZHBYACEYGNI53GLSNJP4W/action/storage_attestation","attest_author":"https://pith.science/pith/C6UZWZHBYACEYGNI53GLSNJP4W/action/author_attestation","sign_citation":"https://pith.science/pith/C6UZWZHBYACEYGNI53GLSNJP4W/action/citation_signature","submit_replication":"https://pith.science/pith/C6UZWZHBYACEYGNI53GLSNJP4W/action/replication_record"}},"created_at":"2026-05-18T00:33:23.930684+00:00","updated_at":"2026-05-18T00:33:23.930684+00:00"}