{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:Y33IJ4GVLHLWN7GZN565KHKGYB","short_pith_number":"pith:Y33IJ4GV","schema_version":"1.0","canonical_sha256":"c6f684f0d559d766fcd96f7dd51d46c054b08008ad31f36e13d77a5fe2ad2b91","source":{"kind":"arxiv","id":"2202.09179","version":2},"attestation_state":"computed","paper":{"title":"Incorporating Texture Information into Dimensionality Reduction for High-Dimensional Images","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Alexander Vieth, Anna Vilanova, Boudewijn Lelieveldt, Elmar Eisemann, Thomas H\\\"ollt","submitted_at":"2022-02-18T13:17:43Z","abstract_excerpt":"High-dimensional imaging is becoming increasingly relevant in many fields from astronomy and cultural heritage to systems biology. Visual exploration of such high-dimensional data is commonly facilitated by dimensionality reduction. However, common dimensionality reduction methods do not include spatial information present in images, such as local texture features, into the construction of low-dimensional embeddings. Consequently, exploration of such data is typically split into a step focusing on the attribute space followed by a step focusing on spatial information, or vice versa. In this pa"},"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":"2202.09179","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2022-02-18T13:17:43Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"1097a33fa29a6b6277da285a68387ffac10284a85bfeae30c687c25bfe25da34","abstract_canon_sha256":"dd273375b8f705adb664dad7b3a0cb925106afd6cd3c409765c83c1a138d44c9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:37:10.027276Z","signature_b64":"V1xolOoVzIZVXPrcpgmZKD91JAy+Go9+5xhcSaTRf4ROxQ2Ktxy9Os8859rfAXNnoMbPzXnsKGMXZjI93s/fCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c6f684f0d559d766fcd96f7dd51d46c054b08008ad31f36e13d77a5fe2ad2b91","last_reissued_at":"2026-07-05T06:37:10.026851Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:37:10.026851Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Incorporating Texture Information into Dimensionality Reduction for High-Dimensional Images","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Alexander Vieth, Anna Vilanova, Boudewijn Lelieveldt, Elmar Eisemann, Thomas H\\\"ollt","submitted_at":"2022-02-18T13:17:43Z","abstract_excerpt":"High-dimensional imaging is becoming increasingly relevant in many fields from astronomy and cultural heritage to systems biology. Visual exploration of such high-dimensional data is commonly facilitated by dimensionality reduction. However, common dimensionality reduction methods do not include spatial information present in images, such as local texture features, into the construction of low-dimensional embeddings. Consequently, exploration of such data is typically split into a step focusing on the attribute space followed by a step focusing on spatial information, or vice versa. In this pa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.09179","kind":"arxiv","version":2},"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/2202.09179/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":"2202.09179","created_at":"2026-07-05T06:37:10.026915+00:00"},{"alias_kind":"arxiv_version","alias_value":"2202.09179v2","created_at":"2026-07-05T06:37:10.026915+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.09179","created_at":"2026-07-05T06:37:10.026915+00:00"},{"alias_kind":"pith_short_12","alias_value":"Y33IJ4GVLHLW","created_at":"2026-07-05T06:37:10.026915+00:00"},{"alias_kind":"pith_short_16","alias_value":"Y33IJ4GVLHLWN7GZ","created_at":"2026-07-05T06:37:10.026915+00:00"},{"alias_kind":"pith_short_8","alias_value":"Y33IJ4GV","created_at":"2026-07-05T06:37:10.026915+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/Y33IJ4GVLHLWN7GZN565KHKGYB","json":"https://pith.science/pith/Y33IJ4GVLHLWN7GZN565KHKGYB.json","graph_json":"https://pith.science/api/pith-number/Y33IJ4GVLHLWN7GZN565KHKGYB/graph.json","events_json":"https://pith.science/api/pith-number/Y33IJ4GVLHLWN7GZN565KHKGYB/events.json","paper":"https://pith.science/paper/Y33IJ4GV"},"agent_actions":{"view_html":"https://pith.science/pith/Y33IJ4GVLHLWN7GZN565KHKGYB","download_json":"https://pith.science/pith/Y33IJ4GVLHLWN7GZN565KHKGYB.json","view_paper":"https://pith.science/paper/Y33IJ4GV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2202.09179&json=true","fetch_graph":"https://pith.science/api/pith-number/Y33IJ4GVLHLWN7GZN565KHKGYB/graph.json","fetch_events":"https://pith.science/api/pith-number/Y33IJ4GVLHLWN7GZN565KHKGYB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Y33IJ4GVLHLWN7GZN565KHKGYB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Y33IJ4GVLHLWN7GZN565KHKGYB/action/storage_attestation","attest_author":"https://pith.science/pith/Y33IJ4GVLHLWN7GZN565KHKGYB/action/author_attestation","sign_citation":"https://pith.science/pith/Y33IJ4GVLHLWN7GZN565KHKGYB/action/citation_signature","submit_replication":"https://pith.science/pith/Y33IJ4GVLHLWN7GZN565KHKGYB/action/replication_record"}},"created_at":"2026-07-05T06:37:10.026915+00:00","updated_at":"2026-07-05T06:37:10.026915+00:00"}