{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:76HUVHRQXQC4YPOQ42A3LZIHW2","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":"b0f7232c8b67bf885f95cbd4f2154b8b39c2382947b4f4ad18347519ef977d76","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2021-02-21T16:39:20Z","title_canon_sha256":"12f85b2baee0491d45ec0b5f2ba9c24305f2ee5087bb031c2ff786c6441ce245"},"schema_version":"1.0","source":{"id":"2102.10640","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2102.10640","created_at":"2026-07-05T02:17:10Z"},{"alias_kind":"arxiv_version","alias_value":"2102.10640v2","created_at":"2026-07-05T02:17:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2102.10640","created_at":"2026-07-05T02:17:10Z"},{"alias_kind":"pith_short_12","alias_value":"76HUVHRQXQC4","created_at":"2026-07-05T02:17:10Z"},{"alias_kind":"pith_short_16","alias_value":"76HUVHRQXQC4YPOQ","created_at":"2026-07-05T02:17:10Z"},{"alias_kind":"pith_short_8","alias_value":"76HUVHRQ","created_at":"2026-07-05T02:17:10Z"}],"graph_snapshots":[{"event_id":"sha256:3e1a74dd0bb6bd413fa9065f3a87d1c81f5a217ced42ab0a578c36a7633c34ee","target":"graph","created_at":"2026-07-05T02:17:10Z","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/2102.10640/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The recent outbreak of COVID-19 has motivated researchers to contribute in the area of medical imaging using artificial intelligence and deep learning. Super-resolution (SR), in the past few years, has produced remarkable results using deep learning methods. The ability of deep learning methods to learn the non-linear mapping from low-resolution (LR) images to their corresponding high-resolution (HR) images leads to compelling results for SR in diverse areas of research. In this paper, we propose a deep learning based image super-resolution architecture in Tchebichef transform domain. This is ","authors_text":"Ahlad Kumar, Harsh Vardhan Singh","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2021-02-21T16:39:20Z","title":"Tchebichef Transform Domain-based Deep Learning Architecture for Image Super-resolution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2102.10640","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":"sha256:3bc10abc2d21f355d21bde61ee788b5e59bc3134ede46e589960c57c5ef61f18","target":"record","created_at":"2026-07-05T02:17:10Z","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":"b0f7232c8b67bf885f95cbd4f2154b8b39c2382947b4f4ad18347519ef977d76","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2021-02-21T16:39:20Z","title_canon_sha256":"12f85b2baee0491d45ec0b5f2ba9c24305f2ee5087bb031c2ff786c6441ce245"},"schema_version":"1.0","source":{"id":"2102.10640","kind":"arxiv","version":2}},"canonical_sha256":"ff8f4a9e30bc05cc3dd0e681b5e507b68be14e529e3e968ca384297b1698eba6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ff8f4a9e30bc05cc3dd0e681b5e507b68be14e529e3e968ca384297b1698eba6","first_computed_at":"2026-07-05T02:17:10.239512Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:17:10.239512Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4GEzsQPWiq4c0X1Rzc1Vnall1nLEpicqD+xZ7eQSOa3WWUKFBYfZNZ72r/PA3KOIRuOJwR7Cmpw9aKxNKQKEDg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:17:10.239995Z","signed_message":"canonical_sha256_bytes"},"source_id":"2102.10640","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3bc10abc2d21f355d21bde61ee788b5e59bc3134ede46e589960c57c5ef61f18","sha256:3e1a74dd0bb6bd413fa9065f3a87d1c81f5a217ced42ab0a578c36a7633c34ee"],"state_sha256":"16aef387f70687133b96757989987a0aac87f94fdd297ffb8b6303da181b1913"}