{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:7NQVQETEY3B4OM5CWIH3FSN25H","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":"f395c629f7d9e92dba707de2ae47fc3970e6b5f15da2735e3a4ff90101dd50fc","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-10-30T20:03:20Z","title_canon_sha256":"627f05e94c4112552e5f432380ea37e5c9aa18e1f064350bb854653a1070034a"},"schema_version":"1.0","source":{"id":"2011.00081","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.00081","created_at":"2026-07-05T03:07:03Z"},{"alias_kind":"arxiv_version","alias_value":"2011.00081v2","created_at":"2026-07-05T03:07:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.00081","created_at":"2026-07-05T03:07:03Z"},{"alias_kind":"pith_short_12","alias_value":"7NQVQETEY3B4","created_at":"2026-07-05T03:07:03Z"},{"alias_kind":"pith_short_16","alias_value":"7NQVQETEY3B4OM5C","created_at":"2026-07-05T03:07:03Z"},{"alias_kind":"pith_short_8","alias_value":"7NQVQETE","created_at":"2026-07-05T03:07:03Z"}],"graph_snapshots":[{"event_id":"sha256:15f66e14d248b3dc1834564fa493b3585795c56fd14049e7fd8c05afa9a44a8e","target":"graph","created_at":"2026-07-05T03:07:03Z","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/2011.00081/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Cancers are the leading cause of death in many countries. Early diagnosis plays a crucial role in having proper treatment for this debilitating disease. The automated classification of the type of cancer is a challenging task since pathologists must examine a huge number of histopathological images to detect infinitesimal abnormalities. In this study, we propose a novel convolutional neural network (CNN) architecture composed of a Concatenation of multiple Networks, called C-Net, to classify biomedical images. The model incorporates multiple CNNs including Outer, Middle, and Inner. The first t","authors_text":"Hosein Barzekar, Zeyun Yu","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-10-30T20:03:20Z","title":"C-Net: A Reliable Convolutional Neural Network for Biomedical Image Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.00081","kind":"arxiv","version":2},"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":"sha256:95d3bdfc83d8b06e58c157e5d413a25dfc31fb8d3e774fa0d4aa72b019f9e36d","target":"record","created_at":"2026-07-05T03:07:03Z","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":"f395c629f7d9e92dba707de2ae47fc3970e6b5f15da2735e3a4ff90101dd50fc","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-10-30T20:03:20Z","title_canon_sha256":"627f05e94c4112552e5f432380ea37e5c9aa18e1f064350bb854653a1070034a"},"schema_version":"1.0","source":{"id":"2011.00081","kind":"arxiv","version":2}},"canonical_sha256":"fb61581264c6c3c733a2b20fb2c9bae9d95738a87c7a9fb5a8c621606d5618c0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fb61581264c6c3c733a2b20fb2c9bae9d95738a87c7a9fb5a8c621606d5618c0","first_computed_at":"2026-07-05T03:07:03.927427Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:07:03.927427Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4hePC9AU260BvluwCrYUB+EyspY/ZycKvySMw5nlzEYCgtok4Ck5rRT96hjAfk92HT1RnDO+0j0j5vKAOiIgDw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:07:03.927860Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.00081","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:95d3bdfc83d8b06e58c157e5d413a25dfc31fb8d3e774fa0d4aa72b019f9e36d","sha256:15f66e14d248b3dc1834564fa493b3585795c56fd14049e7fd8c05afa9a44a8e"],"state_sha256":"f1b018a72c82ea86151cc14fe3ab0830f935d66f38e53de8b88181a2d979ee5f"}