{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:AQ2EHEHE4JTBVTC7EIRHH5VGZS","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":"5bec9d27be2a7137f73d0e78696828cf1137673a44f59a4575eb477819069e97","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-06-08T18:38:24Z","title_canon_sha256":"671096c6f5fba4d396470f153e603e966e69aeb59694a9f85e7e84049b31386e"},"schema_version":"1.0","source":{"id":"2006.04868","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.04868","created_at":"2026-07-05T01:14:01Z"},{"alias_kind":"arxiv_version","alias_value":"2006.04868v2","created_at":"2026-07-05T01:14:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.04868","created_at":"2026-07-05T01:14:01Z"},{"alias_kind":"pith_short_12","alias_value":"AQ2EHEHE4JTB","created_at":"2026-07-05T01:14:01Z"},{"alias_kind":"pith_short_16","alias_value":"AQ2EHEHE4JTBVTC7","created_at":"2026-07-05T01:14:01Z"},{"alias_kind":"pith_short_8","alias_value":"AQ2EHEHE","created_at":"2026-07-05T01:14:01Z"}],"graph_snapshots":[{"event_id":"sha256:2e0d6608aa7829444826c0717ff58fc87faa59f47bd1d1b2a36ca219480b10f2","target":"graph","created_at":"2026-07-05T01:14:01Z","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/2006.04868/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semantic image segmentation is the process of labeling each pixel of an image with its corresponding class. An encoder-decoder based approach, like U-Net and its variants, is a popular strategy for solving medical image segmentation tasks. To improve the performance of U-Net on various segmentation tasks, we propose a novel architecture called DoubleU-Net, which is a combination of two U-Net architectures stacked on top of each other. The first U-Net uses a pre-trained VGG-19 as the encoder, which has already learned features from ImageNet and can be transferred to another task easily. To capt","authors_text":"Dag Johansen, Debesh Jha, H{\\aa}vard D. Johansen, Michael A. Riegler, P{\\aa}l Halvorsen","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-06-08T18:38:24Z","title":"DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.04868","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:afeec688be46039108f609c51a16e1ee14253aaf5ba5aee645f7a2714055deb3","target":"record","created_at":"2026-07-05T01:14:01Z","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":"5bec9d27be2a7137f73d0e78696828cf1137673a44f59a4575eb477819069e97","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2020-06-08T18:38:24Z","title_canon_sha256":"671096c6f5fba4d396470f153e603e966e69aeb59694a9f85e7e84049b31386e"},"schema_version":"1.0","source":{"id":"2006.04868","kind":"arxiv","version":2}},"canonical_sha256":"04344390e4e2661acc5f222273f6a6cc84a0f5883f66fb96f4b51ef8bf54a043","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"04344390e4e2661acc5f222273f6a6cc84a0f5883f66fb96f4b51ef8bf54a043","first_computed_at":"2026-07-05T01:14:01.164033Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:14:01.164033Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lLhOvMvjZu0YP2/Cxt996R7Dou6I4od5neSYbGfPfpOWFzVoVTWHobd7R5py//UKQYcJtcmETcV6aOGk4Yq6BA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:14:01.164457Z","signed_message":"canonical_sha256_bytes"},"source_id":"2006.04868","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:afeec688be46039108f609c51a16e1ee14253aaf5ba5aee645f7a2714055deb3","sha256:2e0d6608aa7829444826c0717ff58fc87faa59f47bd1d1b2a36ca219480b10f2"],"state_sha256":"0faf5854e08784fe81c8d502416500ef58ec6e73f9233e8ae613dc8627e2421c"}