{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:KNW5R7TJGAUTMGX7CRNIKEX6P7","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":"f628c195ece9dbfd2dbf4ba062d6541f0231a593c048b25046ab2ba6e893f44c","cross_cats_sorted":["eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-06-01T06:34:14Z","title_canon_sha256":"628be33cfe17a96bc1ac73e11869dbe21734513445f3d1d7f9a55b5a9586084c"},"schema_version":"1.0","source":{"id":"2306.00385","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.00385","created_at":"2026-07-05T09:49:39Z"},{"alias_kind":"arxiv_version","alias_value":"2306.00385v2","created_at":"2026-07-05T09:49:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.00385","created_at":"2026-07-05T09:49:39Z"},{"alias_kind":"pith_short_12","alias_value":"KNW5R7TJGAUT","created_at":"2026-07-05T09:49:39Z"},{"alias_kind":"pith_short_16","alias_value":"KNW5R7TJGAUTMGX7","created_at":"2026-07-05T09:49:39Z"},{"alias_kind":"pith_short_8","alias_value":"KNW5R7TJ","created_at":"2026-07-05T09:49:39Z"}],"graph_snapshots":[{"event_id":"sha256:ae7e1021d6052fe44fc85c9be8571e119ca88c9808bf09bf2316e5a8b60e54b5","target":"graph","created_at":"2026-07-05T09:49:39Z","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/2306.00385/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The development of learning-based hyperspectral image compression methods has recently attracted great attention in remote sensing. Such methods require a high number of hyperspectral images to be used during training to optimize all parameters and reach a high compression performance. However, existing hyperspectral datasets are not sufficient to train and evaluate learning-based compression methods, which hinders the research in this field. To address this problem, in this paper we present HySpecNet-11k that is a large-scale hyperspectral benchmark dataset made up of 11,483 nonoverlapping im","authors_text":"Beg\\\"um Demir, Martin Hermann Paul Fuchs","cross_cats":["eess.IV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-06-01T06:34:14Z","title":"HySpecNet-11k: A Large-Scale Hyperspectral Dataset for Benchmarking Learning-Based Hyperspectral Image Compression Methods"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.00385","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:dbf265861f467a95633fb218f147805590cec69423ad1a423ee1e453c26000dd","target":"record","created_at":"2026-07-05T09:49:39Z","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":"f628c195ece9dbfd2dbf4ba062d6541f0231a593c048b25046ab2ba6e893f44c","cross_cats_sorted":["eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-06-01T06:34:14Z","title_canon_sha256":"628be33cfe17a96bc1ac73e11869dbe21734513445f3d1d7f9a55b5a9586084c"},"schema_version":"1.0","source":{"id":"2306.00385","kind":"arxiv","version":2}},"canonical_sha256":"536dd8fe693029361aff145a8512fe7fd082fb51246b0ec318949fc5ac1c5be1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"536dd8fe693029361aff145a8512fe7fd082fb51246b0ec318949fc5ac1c5be1","first_computed_at":"2026-07-05T09:49:39.777590Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:49:39.777590Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"E1QkVhA5glPpoLVJM7tdTdoq4yNoJPT8GNkvFb4Zhw2ANu2RWJXzxVsD33M3HbYvnQdT3mdJeSsS8Ys2dENEAw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:49:39.778060Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.00385","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dbf265861f467a95633fb218f147805590cec69423ad1a423ee1e453c26000dd","sha256:ae7e1021d6052fe44fc85c9be8571e119ca88c9808bf09bf2316e5a8b60e54b5"],"state_sha256":"c5c64be810557e74747b80821f266384ca0233e150fb225686e47949a77f96ab"}