{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:W7BP2I3E4P3HYIR37I6QW4FILW","short_pith_number":"pith:W7BP2I3E","canonical_record":{"source":{"id":"1802.08369","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-23T02:42:13Z","cross_cats_sorted":[],"title_canon_sha256":"dee5500956c5b58c53a07130765990debbbec509eb28d277d65c25ac9ab7737e","abstract_canon_sha256":"b9ad8a304b1e23c0b255b844e03ac6f5187ba68341a4644bf5a49a7fa14fe400"},"schema_version":"1.0"},"canonical_sha256":"b7c2fd2364e3f67c223bfa3d0b70a85da4f00fd0aed664164b3f134a74e71f85","source":{"kind":"arxiv","id":"1802.08369","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.08369","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"arxiv_version","alias_value":"1802.08369v1","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.08369","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"pith_short_12","alias_value":"W7BP2I3E4P3H","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"W7BP2I3E4P3HYIR3","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"W7BP2I3E","created_at":"2026-05-18T12:32:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:W7BP2I3E4P3HYIR37I6QW4FILW","target":"record","payload":{"canonical_record":{"source":{"id":"1802.08369","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-23T02:42:13Z","cross_cats_sorted":[],"title_canon_sha256":"dee5500956c5b58c53a07130765990debbbec509eb28d277d65c25ac9ab7737e","abstract_canon_sha256":"b9ad8a304b1e23c0b255b844e03ac6f5187ba68341a4644bf5a49a7fa14fe400"},"schema_version":"1.0"},"canonical_sha256":"b7c2fd2364e3f67c223bfa3d0b70a85da4f00fd0aed664164b3f134a74e71f85","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:08:15.373768Z","signature_b64":"ZE1IULGfz9tPuoixasuebWDr8FFdsdbRTJ46b2TQ8xH7WDRUYvHB2uUefe3i50NHM8PVRAuNWfhbqyHDs2KkCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7c2fd2364e3f67c223bfa3d0b70a85da4f00fd0aed664164b3f134a74e71f85","last_reissued_at":"2026-05-18T00:08:15.373395Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:08:15.373395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.08369","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:08:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pgxktF8ONzaXxg18zQjcF5fgggK5WULfKyDflVQUHkSnV6DHFuCRveS6FJOAHmyxyHk7Rb/JATrxVHYmIl1MAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T21:59:03.123138Z"},"content_sha256":"5f1ca7a1e896cd583e54d7a76d319d7350f9f9177d380e6b56353d3d5f8e4cb2","schema_version":"1.0","event_id":"sha256:5f1ca7a1e896cd583e54d7a76d319d7350f9f9177d380e6b56353d3d5f8e4cb2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:W7BP2I3E4P3HYIR37I6QW4FILW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Missing Data Reconstruction in Remote Sensing image with a Unified Spatial-Temporal-Spectral Deep Convolutional Neural Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chao Zeng, Qiangqiang Yuan, Qiang Zhang, Xinghua Li, Yancong Wei","submitted_at":"2018-02-23T02:42:13Z","abstract_excerpt":"Because of the internal malfunction of satellite sensors and poor atmospheric conditions such as thick cloud, the acquired remote sensing data often suffer from missing information, i.e., the data usability is greatly reduced. In this paper, a novel method of missing information reconstruction in remote sensing images is proposed. The unified spatial-temporal-spectral framework based on a deep convolutional neural network (STS-CNN) employs a unified deep convolutional neural network combined with spatial-temporal-spectral supplementary information. In addition, to address the fact that most me"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.08369","kind":"arxiv","version":1},"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":"2026-05-18T00:08:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HPwZ96jBA4ceeMy5/LEdS7qamf3zpaNp/y87c5TrN/TA0NvO+8C1F97rMk6qSVVBa1tCC+u4c3ZARvHUqOxFAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T21:59:03.123520Z"},"content_sha256":"47c30ed71b02c2c45c1040fcf55df3896d143282e1940a8a409adeeb7d4188d0","schema_version":"1.0","event_id":"sha256:47c30ed71b02c2c45c1040fcf55df3896d143282e1940a8a409adeeb7d4188d0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W7BP2I3E4P3HYIR37I6QW4FILW/bundle.json","state_url":"https://pith.science/pith/W7BP2I3E4P3HYIR37I6QW4FILW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W7BP2I3E4P3HYIR37I6QW4FILW/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":"2026-06-01T21:59:03Z","links":{"resolver":"https://pith.science/pith/W7BP2I3E4P3HYIR37I6QW4FILW","bundle":"https://pith.science/pith/W7BP2I3E4P3HYIR37I6QW4FILW/bundle.json","state":"https://pith.science/pith/W7BP2I3E4P3HYIR37I6QW4FILW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W7BP2I3E4P3HYIR37I6QW4FILW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:W7BP2I3E4P3HYIR37I6QW4FILW","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":"b9ad8a304b1e23c0b255b844e03ac6f5187ba68341a4644bf5a49a7fa14fe400","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-23T02:42:13Z","title_canon_sha256":"dee5500956c5b58c53a07130765990debbbec509eb28d277d65c25ac9ab7737e"},"schema_version":"1.0","source":{"id":"1802.08369","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.08369","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"arxiv_version","alias_value":"1802.08369v1","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.08369","created_at":"2026-05-18T00:08:15Z"},{"alias_kind":"pith_short_12","alias_value":"W7BP2I3E4P3H","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"W7BP2I3E4P3HYIR3","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"W7BP2I3E","created_at":"2026-05-18T12:32:59Z"}],"graph_snapshots":[{"event_id":"sha256:47c30ed71b02c2c45c1040fcf55df3896d143282e1940a8a409adeeb7d4188d0","target":"graph","created_at":"2026-05-18T00:08:15Z","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":"Because of the internal malfunction of satellite sensors and poor atmospheric conditions such as thick cloud, the acquired remote sensing data often suffer from missing information, i.e., the data usability is greatly reduced. In this paper, a novel method of missing information reconstruction in remote sensing images is proposed. The unified spatial-temporal-spectral framework based on a deep convolutional neural network (STS-CNN) employs a unified deep convolutional neural network combined with spatial-temporal-spectral supplementary information. In addition, to address the fact that most me","authors_text":"Chao Zeng, Qiangqiang Yuan, Qiang Zhang, Xinghua Li, Yancong Wei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-23T02:42:13Z","title":"Missing Data Reconstruction in Remote Sensing image with a Unified Spatial-Temporal-Spectral Deep Convolutional Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.08369","kind":"arxiv","version":1},"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":"sha256:5f1ca7a1e896cd583e54d7a76d319d7350f9f9177d380e6b56353d3d5f8e4cb2","target":"record","created_at":"2026-05-18T00:08:15Z","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":"b9ad8a304b1e23c0b255b844e03ac6f5187ba68341a4644bf5a49a7fa14fe400","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-23T02:42:13Z","title_canon_sha256":"dee5500956c5b58c53a07130765990debbbec509eb28d277d65c25ac9ab7737e"},"schema_version":"1.0","source":{"id":"1802.08369","kind":"arxiv","version":1}},"canonical_sha256":"b7c2fd2364e3f67c223bfa3d0b70a85da4f00fd0aed664164b3f134a74e71f85","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7c2fd2364e3f67c223bfa3d0b70a85da4f00fd0aed664164b3f134a74e71f85","first_computed_at":"2026-05-18T00:08:15.373395Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:08:15.373395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZE1IULGfz9tPuoixasuebWDr8FFdsdbRTJ46b2TQ8xH7WDRUYvHB2uUefe3i50NHM8PVRAuNWfhbqyHDs2KkCw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:08:15.373768Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.08369","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5f1ca7a1e896cd583e54d7a76d319d7350f9f9177d380e6b56353d3d5f8e4cb2","sha256:47c30ed71b02c2c45c1040fcf55df3896d143282e1940a8a409adeeb7d4188d0"],"state_sha256":"c759cd9cf21a605c594f775e8e62c9914bd556af2e139fa45b09bc0450ffd00d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eiCvsEfwllLcalPygAUmhdu1RCiVkd0IMXog65f5Z4roA8jysAaBFu5gyU5n51ufJbnvaQPMfoZBxaCPqXEzBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T21:59:03.125426Z","bundle_sha256":"1061c4332754976b17c7bf9fe00b7114717b751d7f25ef67d2fc571c2385d517"}}