{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:P2UAQRLJ4ZGLUIWBAC5INLMYKF","short_pith_number":"pith:P2UAQRLJ","schema_version":"1.0","canonical_sha256":"7ea8084569e64cba22c100ba86ad98514737b916e918906a5a026f71306f2f52","source":{"kind":"arxiv","id":"1503.01363","version":3},"attestation_state":"computed","paper":{"title":"Tolerant Testers of Image Properties","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Meiram Murzabulatov, Piotr Berman, Sofya Raskhodnikova","submitted_at":"2015-03-04T16:22:58Z","abstract_excerpt":"We initiate a systematic study of tolerant testers of image properties or, equivalently, algorithms that approximate the distance from a given image to the desired property (that is, the smallest fraction of pixels that need to change in the image to ensure that the image satisfies the desired property). Image processing is a particularly compelling area of applications for sublinear-time algorithms and, specifically, property testing. However, for testing algorithms to reach their full potential in image processing, they have to be tolerant, which allows them to be resilient to noise. Prior t"},"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":"1503.01363","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DS","submitted_at":"2015-03-04T16:22:58Z","cross_cats_sorted":[],"title_canon_sha256":"57f9b8c5892a2f81e337219ff14c39c771f21291405879025809a3e09ad6cd90","abstract_canon_sha256":"022488f1fb463b2cf8d7db7a801ccde62fc8696eaf3dcd44f7cf06fbcab1fa62"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:09:07.123373Z","signature_b64":"jqAGRBFEStd/MfL/qPHlEDLIpvDU9IhEwoxNacw9hPN8Jd/4Of1SoyLOfKXGblARStuyz6bqsU9uzpautv+sBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7ea8084569e64cba22c100ba86ad98514737b916e918906a5a026f71306f2f52","last_reissued_at":"2026-05-18T01:09:07.122836Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:09:07.122836Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Tolerant Testers of Image Properties","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DS","authors_text":"Meiram Murzabulatov, Piotr Berman, Sofya Raskhodnikova","submitted_at":"2015-03-04T16:22:58Z","abstract_excerpt":"We initiate a systematic study of tolerant testers of image properties or, equivalently, algorithms that approximate the distance from a given image to the desired property (that is, the smallest fraction of pixels that need to change in the image to ensure that the image satisfies the desired property). Image processing is a particularly compelling area of applications for sublinear-time algorithms and, specifically, property testing. However, for testing algorithms to reach their full potential in image processing, they have to be tolerant, which allows them to be resilient to noise. Prior t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.01363","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1503.01363","created_at":"2026-05-18T01:09:07.122913+00:00"},{"alias_kind":"arxiv_version","alias_value":"1503.01363v3","created_at":"2026-05-18T01:09:07.122913+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.01363","created_at":"2026-05-18T01:09:07.122913+00:00"},{"alias_kind":"pith_short_12","alias_value":"P2UAQRLJ4ZGL","created_at":"2026-05-18T12:29:34.919912+00:00"},{"alias_kind":"pith_short_16","alias_value":"P2UAQRLJ4ZGLUIWB","created_at":"2026-05-18T12:29:34.919912+00:00"},{"alias_kind":"pith_short_8","alias_value":"P2UAQRLJ","created_at":"2026-05-18T12:29:34.919912+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/P2UAQRLJ4ZGLUIWBAC5INLMYKF","json":"https://pith.science/pith/P2UAQRLJ4ZGLUIWBAC5INLMYKF.json","graph_json":"https://pith.science/api/pith-number/P2UAQRLJ4ZGLUIWBAC5INLMYKF/graph.json","events_json":"https://pith.science/api/pith-number/P2UAQRLJ4ZGLUIWBAC5INLMYKF/events.json","paper":"https://pith.science/paper/P2UAQRLJ"},"agent_actions":{"view_html":"https://pith.science/pith/P2UAQRLJ4ZGLUIWBAC5INLMYKF","download_json":"https://pith.science/pith/P2UAQRLJ4ZGLUIWBAC5INLMYKF.json","view_paper":"https://pith.science/paper/P2UAQRLJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1503.01363&json=true","fetch_graph":"https://pith.science/api/pith-number/P2UAQRLJ4ZGLUIWBAC5INLMYKF/graph.json","fetch_events":"https://pith.science/api/pith-number/P2UAQRLJ4ZGLUIWBAC5INLMYKF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/P2UAQRLJ4ZGLUIWBAC5INLMYKF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/P2UAQRLJ4ZGLUIWBAC5INLMYKF/action/storage_attestation","attest_author":"https://pith.science/pith/P2UAQRLJ4ZGLUIWBAC5INLMYKF/action/author_attestation","sign_citation":"https://pith.science/pith/P2UAQRLJ4ZGLUIWBAC5INLMYKF/action/citation_signature","submit_replication":"https://pith.science/pith/P2UAQRLJ4ZGLUIWBAC5INLMYKF/action/replication_record"}},"created_at":"2026-05-18T01:09:07.122913+00:00","updated_at":"2026-05-18T01:09:07.122913+00:00"}