{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:NM2MTOZR3LEXTR24G4ERZXISBY","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":"75e15d7b1cf817af90abeba26770126b4adb472150e52feb8674380703391df2","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-11-13T16:04:39Z","title_canon_sha256":"08446b9ebad6b51a0f6f0262ad1887e15612e3625921424afaed3b0cbcc2ca2b"},"schema_version":"1.0","source":{"id":"2011.06984","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.06984","created_at":"2026-07-05T01:51:26Z"},{"alias_kind":"arxiv_version","alias_value":"2011.06984v1","created_at":"2026-07-05T01:51:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.06984","created_at":"2026-07-05T01:51:26Z"},{"alias_kind":"pith_short_12","alias_value":"NM2MTOZR3LEX","created_at":"2026-07-05T01:51:26Z"},{"alias_kind":"pith_short_16","alias_value":"NM2MTOZR3LEXTR24","created_at":"2026-07-05T01:51:26Z"},{"alias_kind":"pith_short_8","alias_value":"NM2MTOZR","created_at":"2026-07-05T01:51:26Z"}],"graph_snapshots":[{"event_id":"sha256:325f2aa20dfaaf06a6054ddf633567ae47e9ec7db7343f248699dfb9f86dd2b2","target":"graph","created_at":"2026-07-05T01:51:26Z","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/2011.06984/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Using histopathological images to automatically classify cancer is a difficult task for accurately detecting cancer, especially to identify metastatic cancer in small image patches obtained from larger digital pathology scans. Computer diagnosis technology has attracted wide attention from researchers. In this paper, we propose a noval method which combines the deep learning algorithm in image classification, the DenseNet169 framework and Rectified Adam optimization algorithm. The connectivity pattern of DenseNet is direct connections from any layer to all consecutive layers, which can effecti","authors_text":"Baolin Sun, Guanwen Qiu, Lipei Zhang, Xiaobing Yu, Yunpeng Wang","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-11-13T16:04:39Z","title":"Metastatic Cancer Image Classification Based On Deep Learning Method"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.06984","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":"sha256:760e93f5ca1a6ca9e214a2e42a0d61ed8ab07e0ea9ff9a5ac6850bd1e54db6a8","target":"record","created_at":"2026-07-05T01:51:26Z","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":"75e15d7b1cf817af90abeba26770126b4adb472150e52feb8674380703391df2","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-11-13T16:04:39Z","title_canon_sha256":"08446b9ebad6b51a0f6f0262ad1887e15612e3625921424afaed3b0cbcc2ca2b"},"schema_version":"1.0","source":{"id":"2011.06984","kind":"arxiv","version":1}},"canonical_sha256":"6b34c9bb31dac979c75c37091cdd120e22e0c0aeeac4f25530eb91c5e8ead9c5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6b34c9bb31dac979c75c37091cdd120e22e0c0aeeac4f25530eb91c5e8ead9c5","first_computed_at":"2026-07-05T01:51:26.753373Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:51:26.753373Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oDR5DaBzPXPfX26iz7zbVQGHwX0jRTUtirRbEjFawCxOa6Nld4jZFetXc8Jyr0uj+1fwgM8Waf0e2+Qk2I8SDg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:51:26.753795Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.06984","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:760e93f5ca1a6ca9e214a2e42a0d61ed8ab07e0ea9ff9a5ac6850bd1e54db6a8","sha256:325f2aa20dfaaf06a6054ddf633567ae47e9ec7db7343f248699dfb9f86dd2b2"],"state_sha256":"79823a31eb8c7fdaeeba5ea7f09ac91acef423ea2cb1a14490d29476cda044d9"}