{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:TMR3SLSJJAYNPI3VKBRHEE2YBE","short_pith_number":"pith:TMR3SLSJ","canonical_record":{"source":{"id":"1712.09161","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-26T02:07:46Z","cross_cats_sorted":[],"title_canon_sha256":"bdb79b6ad1d7b80708d1bef604433e29346e577b70fe60dc7c272b1eae032008","abstract_canon_sha256":"ca38d926ace86b05ec173cb6786014934070e9765cce41629917650c764d0d8a"},"schema_version":"1.0"},"canonical_sha256":"9b23b92e494830d7a375506272135809026eb556daaa57912262885e35ab58d4","source":{"kind":"arxiv","id":"1712.09161","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.09161","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"arxiv_version","alias_value":"1712.09161v2","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.09161","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"pith_short_12","alias_value":"TMR3SLSJJAYN","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TMR3SLSJJAYNPI3V","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TMR3SLSJ","created_at":"2026-05-18T12:31:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:TMR3SLSJJAYNPI3VKBRHEE2YBE","target":"record","payload":{"canonical_record":{"source":{"id":"1712.09161","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-26T02:07:46Z","cross_cats_sorted":[],"title_canon_sha256":"bdb79b6ad1d7b80708d1bef604433e29346e577b70fe60dc7c272b1eae032008","abstract_canon_sha256":"ca38d926ace86b05ec173cb6786014934070e9765cce41629917650c764d0d8a"},"schema_version":"1.0"},"canonical_sha256":"9b23b92e494830d7a375506272135809026eb556daaa57912262885e35ab58d4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:26:23.164675Z","signature_b64":"6KQAMnrD1zcobWAPp+Bo7dxt3tGgOx9M2qLZ6ct1OsiIqP6rYtdxsqOqpsl5RW8/HgLqfEMBVRmWfI5qe0vACQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9b23b92e494830d7a375506272135809026eb556daaa57912262885e35ab58d4","last_reissued_at":"2026-05-18T00:26:23.163909Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:26:23.163909Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.09161","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":"2026-05-18T00:26:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oLX+buvXcrN8UZcuSBC2Zi58lAouwVKNlZpGy7luh5/WKv69dPmKv/GJWSeshGD3DTFNC+Ne+Dsk++0FpWKYCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T05:11:48.367592Z"},"content_sha256":"5a93401473f8ea46102bebe08fafb205fe05864edfa7c2fc82533288413aff97","schema_version":"1.0","event_id":"sha256:5a93401473f8ea46102bebe08fafb205fe05864edfa7c2fc82533288413aff97"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:TMR3SLSJJAYNPI3VKBRHEE2YBE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Segmenting Sky Pixels in Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aisha Urooj Khan, Ali Borji, Cecilia La Place","submitted_at":"2017-12-26T02:07:46Z","abstract_excerpt":"Outdoor scene parsing models are often trained on ideal datasets and produce quality results. However, this leads to a discrepancy when applied to the real world. The quality of scene parsing, particularly sky classification, decreases in night time images, images involving varying weather conditions, and scene changes due to seasonal weather. This project focuses on approaching these challenges by using a state-of-the-art model in conjunction with a non-ideal dataset: SkyFinder and a subset from SUN database with Sky object. We focus specifically on sky segmentation, the task of determining s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.09161","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":"2026-05-18T00:26:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LtTBADORo1oMwWucYzP0l9hfjM/Jkm4ozEllr9bMaWQakpVdJDLrFmHlVJFoaGCWA/RwTGjuO023tphgyEDoCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T05:11:48.368035Z"},"content_sha256":"8a1e59aa1847d7f05aaa5317b219f4639038a766d71f1ae19ce9325d8bc25324","schema_version":"1.0","event_id":"sha256:8a1e59aa1847d7f05aaa5317b219f4639038a766d71f1ae19ce9325d8bc25324"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TMR3SLSJJAYNPI3VKBRHEE2YBE/bundle.json","state_url":"https://pith.science/pith/TMR3SLSJJAYNPI3VKBRHEE2YBE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TMR3SLSJJAYNPI3VKBRHEE2YBE/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":"2026-06-11T05:11:48Z","links":{"resolver":"https://pith.science/pith/TMR3SLSJJAYNPI3VKBRHEE2YBE","bundle":"https://pith.science/pith/TMR3SLSJJAYNPI3VKBRHEE2YBE/bundle.json","state":"https://pith.science/pith/TMR3SLSJJAYNPI3VKBRHEE2YBE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TMR3SLSJJAYNPI3VKBRHEE2YBE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:TMR3SLSJJAYNPI3VKBRHEE2YBE","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":"ca38d926ace86b05ec173cb6786014934070e9765cce41629917650c764d0d8a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-26T02:07:46Z","title_canon_sha256":"bdb79b6ad1d7b80708d1bef604433e29346e577b70fe60dc7c272b1eae032008"},"schema_version":"1.0","source":{"id":"1712.09161","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.09161","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"arxiv_version","alias_value":"1712.09161v2","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.09161","created_at":"2026-05-18T00:26:23Z"},{"alias_kind":"pith_short_12","alias_value":"TMR3SLSJJAYN","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_16","alias_value":"TMR3SLSJJAYNPI3V","created_at":"2026-05-18T12:31:46Z"},{"alias_kind":"pith_short_8","alias_value":"TMR3SLSJ","created_at":"2026-05-18T12:31:46Z"}],"graph_snapshots":[{"event_id":"sha256:8a1e59aa1847d7f05aaa5317b219f4639038a766d71f1ae19ce9325d8bc25324","target":"graph","created_at":"2026-05-18T00:26:23Z","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":"Outdoor scene parsing models are often trained on ideal datasets and produce quality results. However, this leads to a discrepancy when applied to the real world. The quality of scene parsing, particularly sky classification, decreases in night time images, images involving varying weather conditions, and scene changes due to seasonal weather. This project focuses on approaching these challenges by using a state-of-the-art model in conjunction with a non-ideal dataset: SkyFinder and a subset from SUN database with Sky object. We focus specifically on sky segmentation, the task of determining s","authors_text":"Aisha Urooj Khan, Ali Borji, Cecilia La Place","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-26T02:07:46Z","title":"Segmenting Sky Pixels in Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.09161","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":"sha256:5a93401473f8ea46102bebe08fafb205fe05864edfa7c2fc82533288413aff97","target":"record","created_at":"2026-05-18T00:26:23Z","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":"ca38d926ace86b05ec173cb6786014934070e9765cce41629917650c764d0d8a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-26T02:07:46Z","title_canon_sha256":"bdb79b6ad1d7b80708d1bef604433e29346e577b70fe60dc7c272b1eae032008"},"schema_version":"1.0","source":{"id":"1712.09161","kind":"arxiv","version":2}},"canonical_sha256":"9b23b92e494830d7a375506272135809026eb556daaa57912262885e35ab58d4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9b23b92e494830d7a375506272135809026eb556daaa57912262885e35ab58d4","first_computed_at":"2026-05-18T00:26:23.163909Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:26:23.163909Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6KQAMnrD1zcobWAPp+Bo7dxt3tGgOx9M2qLZ6ct1OsiIqP6rYtdxsqOqpsl5RW8/HgLqfEMBVRmWfI5qe0vACQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:26:23.164675Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.09161","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5a93401473f8ea46102bebe08fafb205fe05864edfa7c2fc82533288413aff97","sha256:8a1e59aa1847d7f05aaa5317b219f4639038a766d71f1ae19ce9325d8bc25324"],"state_sha256":"063376b9ecd143829518073dec0dc4ab9c4432ac2ebc3331f4dd8c6f65a981af"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"txVxDd6eaU6qNdgkRlxK4nV36mUj8d3RJJRGgokvAXP32v9rJ+UmuVJWUCjSOz2Kv0cOOHnP9z3KX8QbjcrmAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T05:11:48.371291Z","bundle_sha256":"748687e9b27e07254872430c9e2ff96d49ca10ecdf5ee340c0ad7299b0756456"}}