{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:GCLK2GH7H4CZK56Q3M4TMKI6Q3","short_pith_number":"pith:GCLK2GH7","canonical_record":{"source":{"id":"1908.09287","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-25T09:18:03Z","cross_cats_sorted":["cs.CV","cs.LG","stat.ML"],"title_canon_sha256":"95e81f01bf296e32936d960fe86784d6c688bb83361b06dc396a988bcb393b29","abstract_canon_sha256":"69efaaab618d810c0195f637b2347572fc381bf90031c2f7354088390e342175"},"schema_version":"1.0"},"canonical_sha256":"3096ad18ff3f059577d0db3936291e86e302a9c646d7544711f6927c2e851853","source":{"kind":"arxiv","id":"1908.09287","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.09287","created_at":"2026-07-04T23:59:38Z"},{"alias_kind":"arxiv_version","alias_value":"1908.09287v1","created_at":"2026-07-04T23:59:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.09287","created_at":"2026-07-04T23:59:38Z"},{"alias_kind":"pith_short_12","alias_value":"GCLK2GH7H4CZ","created_at":"2026-07-04T23:59:38Z"},{"alias_kind":"pith_short_16","alias_value":"GCLK2GH7H4CZK56Q","created_at":"2026-07-04T23:59:38Z"},{"alias_kind":"pith_short_8","alias_value":"GCLK2GH7","created_at":"2026-07-04T23:59:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:GCLK2GH7H4CZK56Q3M4TMKI6Q3","target":"record","payload":{"canonical_record":{"source":{"id":"1908.09287","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-25T09:18:03Z","cross_cats_sorted":["cs.CV","cs.LG","stat.ML"],"title_canon_sha256":"95e81f01bf296e32936d960fe86784d6c688bb83361b06dc396a988bcb393b29","abstract_canon_sha256":"69efaaab618d810c0195f637b2347572fc381bf90031c2f7354088390e342175"},"schema_version":"1.0"},"canonical_sha256":"3096ad18ff3f059577d0db3936291e86e302a9c646d7544711f6927c2e851853","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:59:38.879030Z","signature_b64":"X7Y6YBcLiK5Gpkn5QLT2I2JLBnV8Grr7NZK8T9PCpBHmX/RxjkZtpYNqkjUxvMzE2EcF2avx+4hPc12f9LMbAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3096ad18ff3f059577d0db3936291e86e302a9c646d7544711f6927c2e851853","last_reissued_at":"2026-07-04T23:59:38.878634Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:59:38.878634Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.09287","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":"2026-07-04T23:59:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RfXehRNksgPG1jAtIUwTgT9bV3NKaLXuXTIpuV1l7wCEucmAQ65gY3svB4RQyMNqwotvztqadvTDw/TUVWR9AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T16:24:28.562396Z"},"content_sha256":"3546db946093d9365ce7d745076d5257fe1674410ecfc423e87fdc21680ff12d","schema_version":"1.0","event_id":"sha256:3546db946093d9365ce7d745076d5257fe1674410ecfc423e87fdc21680ff12d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:GCLK2GH7H4CZK56Q3M4TMKI6Q3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Principal Component Analysis Using Structural Similarity Index for Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG","stat.ML"],"primary_cat":"eess.IV","authors_text":"Benyamin Ghojogh, Fakhri Karray, Mark Crowley","submitted_at":"2019-08-25T09:18:03Z","abstract_excerpt":"Despite the advances of deep learning in specific tasks using images, the principled assessment of image fidelity and similarity is still a critical ability to develop. As it has been shown that Mean Squared Error (MSE) is insufficient for this task, other measures have been developed with one of the most effective being Structural Similarity Index (SSIM). Such measures can be used for subspace learning but existing methods in machine learning, such as Principal Component Analysis (PCA), are based on Euclidean distance or MSE and thus cannot properly capture the structural features of images. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.09287","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1908.09287/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-04T23:59:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sPwbOEAhoBf9LevFFoDQdE3Fob7Tyv8FN8App5NQLIiN2G1FkYUqWOoaWEfX5S9ftflm94nomsTk9/gjLedsCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T16:24:28.562890Z"},"content_sha256":"be6355ee12451894f044a9fee557e7338256df383d999b265f092075e3a01f56","schema_version":"1.0","event_id":"sha256:be6355ee12451894f044a9fee557e7338256df383d999b265f092075e3a01f56"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GCLK2GH7H4CZK56Q3M4TMKI6Q3/bundle.json","state_url":"https://pith.science/pith/GCLK2GH7H4CZK56Q3M4TMKI6Q3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GCLK2GH7H4CZK56Q3M4TMKI6Q3/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":"2026-08-16T16:24:28Z","links":{"resolver":"https://pith.science/pith/GCLK2GH7H4CZK56Q3M4TMKI6Q3","bundle":"https://pith.science/pith/GCLK2GH7H4CZK56Q3M4TMKI6Q3/bundle.json","state":"https://pith.science/pith/GCLK2GH7H4CZK56Q3M4TMKI6Q3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GCLK2GH7H4CZK56Q3M4TMKI6Q3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:GCLK2GH7H4CZK56Q3M4TMKI6Q3","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":"69efaaab618d810c0195f637b2347572fc381bf90031c2f7354088390e342175","cross_cats_sorted":["cs.CV","cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-25T09:18:03Z","title_canon_sha256":"95e81f01bf296e32936d960fe86784d6c688bb83361b06dc396a988bcb393b29"},"schema_version":"1.0","source":{"id":"1908.09287","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.09287","created_at":"2026-07-04T23:59:38Z"},{"alias_kind":"arxiv_version","alias_value":"1908.09287v1","created_at":"2026-07-04T23:59:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.09287","created_at":"2026-07-04T23:59:38Z"},{"alias_kind":"pith_short_12","alias_value":"GCLK2GH7H4CZ","created_at":"2026-07-04T23:59:38Z"},{"alias_kind":"pith_short_16","alias_value":"GCLK2GH7H4CZK56Q","created_at":"2026-07-04T23:59:38Z"},{"alias_kind":"pith_short_8","alias_value":"GCLK2GH7","created_at":"2026-07-04T23:59:38Z"}],"graph_snapshots":[{"event_id":"sha256:be6355ee12451894f044a9fee557e7338256df383d999b265f092075e3a01f56","target":"graph","created_at":"2026-07-04T23:59:38Z","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/1908.09287/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite the advances of deep learning in specific tasks using images, the principled assessment of image fidelity and similarity is still a critical ability to develop. As it has been shown that Mean Squared Error (MSE) is insufficient for this task, other measures have been developed with one of the most effective being Structural Similarity Index (SSIM). Such measures can be used for subspace learning but existing methods in machine learning, such as Principal Component Analysis (PCA), are based on Euclidean distance or MSE and thus cannot properly capture the structural features of images. ","authors_text":"Benyamin Ghojogh, Fakhri Karray, Mark Crowley","cross_cats":["cs.CV","cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-25T09:18:03Z","title":"Principal Component Analysis Using Structural Similarity Index for Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.09287","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":"sha256:3546db946093d9365ce7d745076d5257fe1674410ecfc423e87fdc21680ff12d","target":"record","created_at":"2026-07-04T23:59:38Z","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":"69efaaab618d810c0195f637b2347572fc381bf90031c2f7354088390e342175","cross_cats_sorted":["cs.CV","cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-25T09:18:03Z","title_canon_sha256":"95e81f01bf296e32936d960fe86784d6c688bb83361b06dc396a988bcb393b29"},"schema_version":"1.0","source":{"id":"1908.09287","kind":"arxiv","version":1}},"canonical_sha256":"3096ad18ff3f059577d0db3936291e86e302a9c646d7544711f6927c2e851853","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3096ad18ff3f059577d0db3936291e86e302a9c646d7544711f6927c2e851853","first_computed_at":"2026-07-04T23:59:38.878634Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:59:38.878634Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"X7Y6YBcLiK5Gpkn5QLT2I2JLBnV8Grr7NZK8T9PCpBHmX/RxjkZtpYNqkjUxvMzE2EcF2avx+4hPc12f9LMbAw==","signature_status":"signed_v1","signed_at":"2026-07-04T23:59:38.879030Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.09287","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3546db946093d9365ce7d745076d5257fe1674410ecfc423e87fdc21680ff12d","sha256:be6355ee12451894f044a9fee557e7338256df383d999b265f092075e3a01f56"],"state_sha256":"2effe951a924e1954b948476b438471d96f01cb0ef47d4d4f229cc27dcbe6720"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+xQgE8ngU6LhoHigxQdQ0NG6qOLU6IOXbFJ+Ba4Ag43LbQOpWlhMfGO8FCfM2jv8RijZNizzPOSq4AXnYqTHCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T16:24:28.566710Z","bundle_sha256":"46fe3b57de161f01665a6e8bf58b8784b4e6046cf4bbe7fc4cfc8beb355eda3e"}}