{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:G3I3PSOIXZQ6IKV5DICSUBWQAD","short_pith_number":"pith:G3I3PSOI","canonical_record":{"source":{"id":"1907.12023","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-28T06:27:01Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"5b4ba9c29b6430f147ca1e1dd1563faec76561b8fb1aed83f06b96f9146acc15","abstract_canon_sha256":"0b7aba9b4b14690b970b7b65e5e0d6c65a1fca24b14f8248923ec525ea5fa8dd"},"schema_version":"1.0"},"canonical_sha256":"36d1b7c9c8be61e42abd1a052a06d000e87a29416e38863fca76655e807b7605","source":{"kind":"arxiv","id":"1907.12023","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.12023","created_at":"2026-07-04T23:50:04Z"},{"alias_kind":"arxiv_version","alias_value":"1907.12023v1","created_at":"2026-07-04T23:50:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.12023","created_at":"2026-07-04T23:50:04Z"},{"alias_kind":"pith_short_12","alias_value":"G3I3PSOIXZQ6","created_at":"2026-07-04T23:50:04Z"},{"alias_kind":"pith_short_16","alias_value":"G3I3PSOIXZQ6IKV5","created_at":"2026-07-04T23:50:04Z"},{"alias_kind":"pith_short_8","alias_value":"G3I3PSOI","created_at":"2026-07-04T23:50:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:G3I3PSOIXZQ6IKV5DICSUBWQAD","target":"record","payload":{"canonical_record":{"source":{"id":"1907.12023","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-28T06:27:01Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"5b4ba9c29b6430f147ca1e1dd1563faec76561b8fb1aed83f06b96f9146acc15","abstract_canon_sha256":"0b7aba9b4b14690b970b7b65e5e0d6c65a1fca24b14f8248923ec525ea5fa8dd"},"schema_version":"1.0"},"canonical_sha256":"36d1b7c9c8be61e42abd1a052a06d000e87a29416e38863fca76655e807b7605","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:50:04.750648Z","signature_b64":"WgiFiU08pmtuUiM5aCEHTJTqrYqXUzyGSbKzTMZ88hWPOBm7bUjRzzzBbIiaOiOwgmsdEDqEShGNahi/AZuLCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36d1b7c9c8be61e42abd1a052a06d000e87a29416e38863fca76655e807b7605","last_reissued_at":"2026-07-04T23:50:04.750174Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:50:04.750174Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.12023","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-04T23:50:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fyWGsSifuC0bNTitieiDpeeeQFFPlxG7YTcxD+ZsvQQYOWEuCc8InouEXykaJeDA6R3sA5pmYqPma6WWJWvBCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T23:31:19.676584Z"},"content_sha256":"418159e34a98236afdfaee2b6fc9cd8410c1e1ad4dc6da4a26e514b4e7173486","schema_version":"1.0","event_id":"sha256:418159e34a98236afdfaee2b6fc9cd8410c1e1ad4dc6da4a26e514b4e7173486"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:G3I3PSOIXZQ6IKV5DICSUBWQAD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Two-Stream CNN with Loose Pair Training for Multi-modal AMD Categorization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Dayong Ding, Di Chen, Feng He, Jianchun Zhao, Jingyuan Yang, Weihong Yu, Weisen Wang, Xirong Li, Youxin Chen, Zhikun Yang, Zhiyan Xu","submitted_at":"2019-07-28T06:27:01Z","abstract_excerpt":"This paper studies automated categorization of age-related macular degeneration (AMD) given a multi-modal input, which consists of a color fundus image and an optical coherence tomography (OCT) image from a specific eye. Previous work uses a traditional method, comprised of feature extraction and classifier training that cannot be optimized jointly. By contrast, we propose a two-stream convolutional neural network (CNN) that is end-to-end. The CNN's fusion layer is tailored to the need of fusing information from the fundus and OCT streams. For generating more multi-modal training instances, we"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.12023","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1907.12023/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-04T23:50:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MET153GvmWGZVufVPwARvc3jw9a0xs5S1qxE4ldrNBMiG1Ajp3KJ947nrwAu1cIHEvzoYEnTbax637IQhMsbAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T23:31:19.676964Z"},"content_sha256":"1297c2a82083d540147e706db47f1bd5a475df0dc40f79c856b65b6edda023f5","schema_version":"1.0","event_id":"sha256:1297c2a82083d540147e706db47f1bd5a475df0dc40f79c856b65b6edda023f5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G3I3PSOIXZQ6IKV5DICSUBWQAD/bundle.json","state_url":"https://pith.science/pith/G3I3PSOIXZQ6IKV5DICSUBWQAD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G3I3PSOIXZQ6IKV5DICSUBWQAD/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T23:31:19Z","links":{"resolver":"https://pith.science/pith/G3I3PSOIXZQ6IKV5DICSUBWQAD","bundle":"https://pith.science/pith/G3I3PSOIXZQ6IKV5DICSUBWQAD/bundle.json","state":"https://pith.science/pith/G3I3PSOIXZQ6IKV5DICSUBWQAD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G3I3PSOIXZQ6IKV5DICSUBWQAD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:G3I3PSOIXZQ6IKV5DICSUBWQAD","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":"0b7aba9b4b14690b970b7b65e5e0d6c65a1fca24b14f8248923ec525ea5fa8dd","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-28T06:27:01Z","title_canon_sha256":"5b4ba9c29b6430f147ca1e1dd1563faec76561b8fb1aed83f06b96f9146acc15"},"schema_version":"1.0","source":{"id":"1907.12023","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.12023","created_at":"2026-07-04T23:50:04Z"},{"alias_kind":"arxiv_version","alias_value":"1907.12023v1","created_at":"2026-07-04T23:50:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.12023","created_at":"2026-07-04T23:50:04Z"},{"alias_kind":"pith_short_12","alias_value":"G3I3PSOIXZQ6","created_at":"2026-07-04T23:50:04Z"},{"alias_kind":"pith_short_16","alias_value":"G3I3PSOIXZQ6IKV5","created_at":"2026-07-04T23:50:04Z"},{"alias_kind":"pith_short_8","alias_value":"G3I3PSOI","created_at":"2026-07-04T23:50:04Z"}],"graph_snapshots":[{"event_id":"sha256:1297c2a82083d540147e706db47f1bd5a475df0dc40f79c856b65b6edda023f5","target":"graph","created_at":"2026-07-04T23:50:04Z","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/1907.12023/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper studies automated categorization of age-related macular degeneration (AMD) given a multi-modal input, which consists of a color fundus image and an optical coherence tomography (OCT) image from a specific eye. Previous work uses a traditional method, comprised of feature extraction and classifier training that cannot be optimized jointly. By contrast, we propose a two-stream convolutional neural network (CNN) that is end-to-end. The CNN's fusion layer is tailored to the need of fusing information from the fundus and OCT streams. For generating more multi-modal training instances, we","authors_text":"Dayong Ding, Di Chen, Feng He, Jianchun Zhao, Jingyuan Yang, Weihong Yu, Weisen Wang, Xirong Li, Youxin Chen, Zhikun Yang, Zhiyan Xu","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-28T06:27:01Z","title":"Two-Stream CNN with Loose Pair Training for Multi-modal AMD Categorization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.12023","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":"sha256:418159e34a98236afdfaee2b6fc9cd8410c1e1ad4dc6da4a26e514b4e7173486","target":"record","created_at":"2026-07-04T23:50:04Z","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":"0b7aba9b4b14690b970b7b65e5e0d6c65a1fca24b14f8248923ec525ea5fa8dd","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-07-28T06:27:01Z","title_canon_sha256":"5b4ba9c29b6430f147ca1e1dd1563faec76561b8fb1aed83f06b96f9146acc15"},"schema_version":"1.0","source":{"id":"1907.12023","kind":"arxiv","version":1}},"canonical_sha256":"36d1b7c9c8be61e42abd1a052a06d000e87a29416e38863fca76655e807b7605","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36d1b7c9c8be61e42abd1a052a06d000e87a29416e38863fca76655e807b7605","first_computed_at":"2026-07-04T23:50:04.750174Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:50:04.750174Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WgiFiU08pmtuUiM5aCEHTJTqrYqXUzyGSbKzTMZ88hWPOBm7bUjRzzzBbIiaOiOwgmsdEDqEShGNahi/AZuLCQ==","signature_status":"signed_v1","signed_at":"2026-07-04T23:50:04.750648Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.12023","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:418159e34a98236afdfaee2b6fc9cd8410c1e1ad4dc6da4a26e514b4e7173486","sha256:1297c2a82083d540147e706db47f1bd5a475df0dc40f79c856b65b6edda023f5"],"state_sha256":"c17782f7545b2416b1262e079ca67b5ef3e40d33e5ab363f66e0f4e84adfd353"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jT/LeBXvIityKf8cLzNpQ8HkTwd3P6tYeWb6EGtjFAXo/up0TUJ2k3zGE0/6vr7JpWp2T2zv4/4QzBtVNQzSDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T23:31:19.678938Z","bundle_sha256":"6e38325fdec518aea3586864459f812de828f5f0e97f032fa22742d355c79432"}}