{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:YLDHB6HZ4ALZ5DZACIE5SNJQRK","short_pith_number":"pith:YLDHB6HZ","canonical_record":{"source":{"id":"1708.05125","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-17T03:35:02Z","cross_cats_sorted":[],"title_canon_sha256":"aff809a4f1d905d43f8f0a1344a39969274fd34a7262c3054e15fd2112f925ee","abstract_canon_sha256":"8d7ef03a5dbc5a8850f5603af1b7a26fc0ce7de68c86b86dc0249d9bff996615"},"schema_version":"1.0"},"canonical_sha256":"c2c670f8f9e0179e8f201209d935308a9c02bffc4d3610a204670c3694394d5e","source":{"kind":"arxiv","id":"1708.05125","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.05125","created_at":"2026-05-18T00:33:06Z"},{"alias_kind":"arxiv_version","alias_value":"1708.05125v2","created_at":"2026-05-18T00:33:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.05125","created_at":"2026-05-18T00:33:06Z"},{"alias_kind":"pith_short_12","alias_value":"YLDHB6HZ4ALZ","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"YLDHB6HZ4ALZ5DZA","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"YLDHB6HZ","created_at":"2026-05-18T12:31:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:YLDHB6HZ4ALZ5DZACIE5SNJQRK","target":"record","payload":{"canonical_record":{"source":{"id":"1708.05125","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-17T03:35:02Z","cross_cats_sorted":[],"title_canon_sha256":"aff809a4f1d905d43f8f0a1344a39969274fd34a7262c3054e15fd2112f925ee","abstract_canon_sha256":"8d7ef03a5dbc5a8850f5603af1b7a26fc0ce7de68c86b86dc0249d9bff996615"},"schema_version":"1.0"},"canonical_sha256":"c2c670f8f9e0179e8f201209d935308a9c02bffc4d3610a204670c3694394d5e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:33:06.313952Z","signature_b64":"BCku0+DDZbWUzQYnXF2txy9QaQ2X38qbYAewwvheNdNU0PTBdRHIWeJMeslFwY/ez8VNX6L/Aftj3ZqVdi8QBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c2c670f8f9e0179e8f201209d935308a9c02bffc4d3610a204670c3694394d5e","last_reissued_at":"2026-05-18T00:33:06.313373Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:33:06.313373Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.05125","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:33:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+yR0Cgx4guX+/3wV3arPOsSnnUJjzmGcuqfKnggeVye5dyerbdGc4voT96R3k/6JTbvoKy/xoCZHKI9CylXaAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T17:21:17.073775Z"},"content_sha256":"0a59ea2ead84f2fc6ee62280c282719e92c946a2c68255600e16b077f966d2c8","schema_version":"1.0","event_id":"sha256:0a59ea2ead84f2fc6ee62280c282719e92c946a2c68255600e16b077f966d2c8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:YLDHB6HZ4ALZ5DZACIE5SNJQRK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hyperspectral Unmixing: Ground Truth Labeling, Datasets, Benchmark Performances and Survey","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Feiyun Zhu","submitted_at":"2017-08-17T03:35:02Z","abstract_excerpt":"Hyperspectral unmixing (HU) is a very useful and increasingly popular preprocessing step for a wide range of hyperspectral applications. However, the HU research has been constrained a lot by three factors: (a) the number of hyperspectral images (especially the ones with ground truths) are very limited; (b) the ground truths of most hyperspectral images are not shared on the web, which may cause lots of unnecessary troubles for researchers to evaluate their algorithms; (c) the codes of most state-of-the-art methods are not shared, which may also delay the testing of new methods.\n  Accordingly,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.05125","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":""},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:33:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YFEWATYrl+Y9OvCvz/oXUAlDTk78JAH7bwgnhWzbpMn3RLCqc59z3SsP5BOo8mp1PWFBZaHOVvfsAPN6y4e6Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T17:21:17.074486Z"},"content_sha256":"62ee499b0b71e49872b21f2a921f024127ec662cddc6c6f7ab33e42a0cddeed1","schema_version":"1.0","event_id":"sha256:62ee499b0b71e49872b21f2a921f024127ec662cddc6c6f7ab33e42a0cddeed1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YLDHB6HZ4ALZ5DZACIE5SNJQRK/bundle.json","state_url":"https://pith.science/pith/YLDHB6HZ4ALZ5DZACIE5SNJQRK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YLDHB6HZ4ALZ5DZACIE5SNJQRK/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-25T17:21:17Z","links":{"resolver":"https://pith.science/pith/YLDHB6HZ4ALZ5DZACIE5SNJQRK","bundle":"https://pith.science/pith/YLDHB6HZ4ALZ5DZACIE5SNJQRK/bundle.json","state":"https://pith.science/pith/YLDHB6HZ4ALZ5DZACIE5SNJQRK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YLDHB6HZ4ALZ5DZACIE5SNJQRK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:YLDHB6HZ4ALZ5DZACIE5SNJQRK","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":"8d7ef03a5dbc5a8850f5603af1b7a26fc0ce7de68c86b86dc0249d9bff996615","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-17T03:35:02Z","title_canon_sha256":"aff809a4f1d905d43f8f0a1344a39969274fd34a7262c3054e15fd2112f925ee"},"schema_version":"1.0","source":{"id":"1708.05125","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.05125","created_at":"2026-05-18T00:33:06Z"},{"alias_kind":"arxiv_version","alias_value":"1708.05125v2","created_at":"2026-05-18T00:33:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.05125","created_at":"2026-05-18T00:33:06Z"},{"alias_kind":"pith_short_12","alias_value":"YLDHB6HZ4ALZ","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_16","alias_value":"YLDHB6HZ4ALZ5DZA","created_at":"2026-05-18T12:31:56Z"},{"alias_kind":"pith_short_8","alias_value":"YLDHB6HZ","created_at":"2026-05-18T12:31:56Z"}],"graph_snapshots":[{"event_id":"sha256:62ee499b0b71e49872b21f2a921f024127ec662cddc6c6f7ab33e42a0cddeed1","target":"graph","created_at":"2026-05-18T00:33:06Z","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"},"paper":{"abstract_excerpt":"Hyperspectral unmixing (HU) is a very useful and increasingly popular preprocessing step for a wide range of hyperspectral applications. However, the HU research has been constrained a lot by three factors: (a) the number of hyperspectral images (especially the ones with ground truths) are very limited; (b) the ground truths of most hyperspectral images are not shared on the web, which may cause lots of unnecessary troubles for researchers to evaluate their algorithms; (c) the codes of most state-of-the-art methods are not shared, which may also delay the testing of new methods.\n  Accordingly,","authors_text":"Feiyun Zhu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-17T03:35:02Z","title":"Hyperspectral Unmixing: Ground Truth Labeling, Datasets, Benchmark Performances and Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.05125","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":"sha256:0a59ea2ead84f2fc6ee62280c282719e92c946a2c68255600e16b077f966d2c8","target":"record","created_at":"2026-05-18T00:33:06Z","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":"8d7ef03a5dbc5a8850f5603af1b7a26fc0ce7de68c86b86dc0249d9bff996615","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-08-17T03:35:02Z","title_canon_sha256":"aff809a4f1d905d43f8f0a1344a39969274fd34a7262c3054e15fd2112f925ee"},"schema_version":"1.0","source":{"id":"1708.05125","kind":"arxiv","version":2}},"canonical_sha256":"c2c670f8f9e0179e8f201209d935308a9c02bffc4d3610a204670c3694394d5e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c2c670f8f9e0179e8f201209d935308a9c02bffc4d3610a204670c3694394d5e","first_computed_at":"2026-05-18T00:33:06.313373Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:33:06.313373Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BCku0+DDZbWUzQYnXF2txy9QaQ2X38qbYAewwvheNdNU0PTBdRHIWeJMeslFwY/ez8VNX6L/Aftj3ZqVdi8QBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:33:06.313952Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.05125","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0a59ea2ead84f2fc6ee62280c282719e92c946a2c68255600e16b077f966d2c8","sha256:62ee499b0b71e49872b21f2a921f024127ec662cddc6c6f7ab33e42a0cddeed1"],"state_sha256":"e5595b5395afe52ad0dc728169340c3f06bc8a3742dd7329fd225de44897e0fc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SU1gOnuzzrTBN33RUh3A4NWIU7as8iCTEMYgW05jUKh9a+x+c5yL4YIJdVnuWrj16pmaFKdTd+Fx4d8P5gjrDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T17:21:17.078557Z","bundle_sha256":"3714fbba1f4b335fd3ab3722da4f86577565cd162686d8b7ea78367302a5e325"}}