{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:WSP5ZZN5GRBAFWYH5LSNU4HOLF","short_pith_number":"pith:WSP5ZZN5","schema_version":"1.0","canonical_sha256":"b49fdce5bd344202db07eae4da70ee5971226f60fcd5bddf656c692df5e60959","source":{"kind":"arxiv","id":"2308.15881","version":1},"attestation_state":"computed","paper":{"title":"Interpretability-guided Data Augmentation for Robust Segmentation in Multi-centre Colonoscopy Data","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Regina Beets-Tan, Valentina Corbetta, Wilson Silva","submitted_at":"2023-08-30T09:03:28Z","abstract_excerpt":"Multi-centre colonoscopy images from various medical centres exhibit distinct complicating factors and overlays that impact the image content, contingent on the specific acquisition centre. Existing Deep Segmentation networks struggle to achieve adequate generalizability in such data sets, and the currently available data augmentation methods do not effectively address these sources of data variability. As a solution, we introduce an innovative data augmentation approach centred on interpretability saliency maps, aimed at enhancing the generalizability of Deep Learning models within the realm "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2308.15881","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2023-08-30T09:03:28Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"3cd959bc7892eea96783b6c6c2d4c7a8570782594bf7c6e2e9e493b62ea309ca","abstract_canon_sha256":"d03a0b21a185ccc4acabe25f6ea5b1ff4ae74d21a3c91fa9ab7a936f03943bb2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:46:14.716349Z","signature_b64":"SMr10VxAmQKz2pu1gGpLENyZSvrmDQw+Ju+VFF8L+pGUSlfbvcpUL6CizUWAwouP+GOckGG+yZKRMOZKfOj4Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b49fdce5bd344202db07eae4da70ee5971226f60fcd5bddf656c692df5e60959","last_reissued_at":"2026-07-05T06:46:14.715839Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:46:14.715839Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Interpretability-guided Data Augmentation for Robust Segmentation in Multi-centre Colonoscopy Data","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Regina Beets-Tan, Valentina Corbetta, Wilson Silva","submitted_at":"2023-08-30T09:03:28Z","abstract_excerpt":"Multi-centre colonoscopy images from various medical centres exhibit distinct complicating factors and overlays that impact the image content, contingent on the specific acquisition centre. Existing Deep Segmentation networks struggle to achieve adequate generalizability in such data sets, and the currently available data augmentation methods do not effectively address these sources of data variability. As a solution, we introduce an innovative data augmentation approach centred on interpretability saliency maps, aimed at enhancing the generalizability of Deep Learning models within the realm "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.15881","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/2308.15881/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2308.15881","created_at":"2026-07-05T06:46:14.715898+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.15881v1","created_at":"2026-07-05T06:46:14.715898+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.15881","created_at":"2026-07-05T06:46:14.715898+00:00"},{"alias_kind":"pith_short_12","alias_value":"WSP5ZZN5GRBA","created_at":"2026-07-05T06:46:14.715898+00:00"},{"alias_kind":"pith_short_16","alias_value":"WSP5ZZN5GRBAFWYH","created_at":"2026-07-05T06:46:14.715898+00:00"},{"alias_kind":"pith_short_8","alias_value":"WSP5ZZN5","created_at":"2026-07-05T06:46:14.715898+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WSP5ZZN5GRBAFWYH5LSNU4HOLF","json":"https://pith.science/pith/WSP5ZZN5GRBAFWYH5LSNU4HOLF.json","graph_json":"https://pith.science/api/pith-number/WSP5ZZN5GRBAFWYH5LSNU4HOLF/graph.json","events_json":"https://pith.science/api/pith-number/WSP5ZZN5GRBAFWYH5LSNU4HOLF/events.json","paper":"https://pith.science/paper/WSP5ZZN5"},"agent_actions":{"view_html":"https://pith.science/pith/WSP5ZZN5GRBAFWYH5LSNU4HOLF","download_json":"https://pith.science/pith/WSP5ZZN5GRBAFWYH5LSNU4HOLF.json","view_paper":"https://pith.science/paper/WSP5ZZN5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.15881&json=true","fetch_graph":"https://pith.science/api/pith-number/WSP5ZZN5GRBAFWYH5LSNU4HOLF/graph.json","fetch_events":"https://pith.science/api/pith-number/WSP5ZZN5GRBAFWYH5LSNU4HOLF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WSP5ZZN5GRBAFWYH5LSNU4HOLF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WSP5ZZN5GRBAFWYH5LSNU4HOLF/action/storage_attestation","attest_author":"https://pith.science/pith/WSP5ZZN5GRBAFWYH5LSNU4HOLF/action/author_attestation","sign_citation":"https://pith.science/pith/WSP5ZZN5GRBAFWYH5LSNU4HOLF/action/citation_signature","submit_replication":"https://pith.science/pith/WSP5ZZN5GRBAFWYH5LSNU4HOLF/action/replication_record"}},"created_at":"2026-07-05T06:46:14.715898+00:00","updated_at":"2026-07-05T06:46:14.715898+00:00"}