{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:LF3PFM7IGC7IPDSDVUHC2IND4X","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":"3e577d3eaeeee5ae6ba38ce3df3f1825ef91f7d1b34db1e0da1453e070257064","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-22T20:04:01Z","title_canon_sha256":"1fd55b3dc88f3f417d2763c86432c9f0c9f571f8cb47af0a418731f052dda14d"},"schema_version":"1.0","source":{"id":"1711.08490","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.08490","created_at":"2026-05-18T00:27:08Z"},{"alias_kind":"arxiv_version","alias_value":"1711.08490v2","created_at":"2026-05-18T00:27:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.08490","created_at":"2026-05-18T00:27:08Z"},{"alias_kind":"pith_short_12","alias_value":"LF3PFM7IGC7I","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LF3PFM7IGC7IPDSD","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LF3PFM7I","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:6da908f75aa6b178017f377509bfe4670c37a87f7d988ecd2ba84f33dee0b575","target":"graph","created_at":"2026-05-18T00:27:08Z","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"},"paper":{"abstract_excerpt":"Deep neural networks have been investigated in learning latent representations of medical images, yet most of the studies limit their approach in a single supervised convolutional neural network (CNN), which usually rely heavily on a large scale annotated dataset for training. To learn image representations with less supervision involved, we propose a deep Siamese CNN (SCNN) architecture that can be trained with only binary image pair information. We evaluated the learned image representations on a task of content-based medical image retrieval using a publicly available multiclass diabetic ret","authors_text":"Wei-Hung Weng, Yu-An Chung","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-22T20:04:01Z","title":"Learning Deep Representations of Medical Images using Siamese CNNs with Application to Content-Based Image Retrieval"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.08490","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":"sha256:6af337a1c2aa959ace33624e29ce68779d380db5a57ea8c95e705c1adad8fa3d","target":"record","created_at":"2026-05-18T00:27:08Z","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":"3e577d3eaeeee5ae6ba38ce3df3f1825ef91f7d1b34db1e0da1453e070257064","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-22T20:04:01Z","title_canon_sha256":"1fd55b3dc88f3f417d2763c86432c9f0c9f571f8cb47af0a418731f052dda14d"},"schema_version":"1.0","source":{"id":"1711.08490","kind":"arxiv","version":2}},"canonical_sha256":"5976f2b3e830be878e43ad0e2d21a3e5e6ddcf39c5189776e4cc534b75b99bfb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5976f2b3e830be878e43ad0e2d21a3e5e6ddcf39c5189776e4cc534b75b99bfb","first_computed_at":"2026-05-18T00:27:08.998709Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:27:08.998709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kGcqemFu+JVEj/LGrWv8rILMIaDs2gDAjaf2ssu/Hp++mu2J7fWrODFZGk1/JNfI5Jzb1B7mu+uX99LVHLi8Bw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:27:08.999377Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.08490","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6af337a1c2aa959ace33624e29ce68779d380db5a57ea8c95e705c1adad8fa3d","sha256:6da908f75aa6b178017f377509bfe4670c37a87f7d988ecd2ba84f33dee0b575"],"state_sha256":"fd7f217b4e4eaf339a8ef833d79c140fe78b0564d44525793567999389015de3"}