{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:VZZFIHXUZZVR5PZRC7KERN2HYL","short_pith_number":"pith:VZZFIHXU","canonical_record":{"source":{"id":"1712.03738","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-11T12:13:33Z","cross_cats_sorted":[],"title_canon_sha256":"346248d6dc593316043761caf51469bdce958d063adfa4cc7fd3f23fe5450167","abstract_canon_sha256":"123962488a04184187af1afa85c0b55e8dfb220daa1aa84374338bbdf15cd078"},"schema_version":"1.0"},"canonical_sha256":"ae72541ef4ce6b1ebf3117d448b747c2c67a4f2d529bbdf5bffb3e8ed646dad8","source":{"kind":"arxiv","id":"1712.03738","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.03738","created_at":"2026-05-18T00:11:18Z"},{"alias_kind":"arxiv_version","alias_value":"1712.03738v1","created_at":"2026-05-18T00:11:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.03738","created_at":"2026-05-18T00:11:18Z"},{"alias_kind":"pith_short_12","alias_value":"VZZFIHXUZZVR","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VZZFIHXUZZVR5PZR","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VZZFIHXU","created_at":"2026-05-18T12:31:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:VZZFIHXUZZVR5PZRC7KERN2HYL","target":"record","payload":{"canonical_record":{"source":{"id":"1712.03738","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-11T12:13:33Z","cross_cats_sorted":[],"title_canon_sha256":"346248d6dc593316043761caf51469bdce958d063adfa4cc7fd3f23fe5450167","abstract_canon_sha256":"123962488a04184187af1afa85c0b55e8dfb220daa1aa84374338bbdf15cd078"},"schema_version":"1.0"},"canonical_sha256":"ae72541ef4ce6b1ebf3117d448b747c2c67a4f2d529bbdf5bffb3e8ed646dad8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:11:18.240596Z","signature_b64":"j78ckcxPHBkfZM6fMYqsnSnl3/Lsk7/T76bxjW+AKdU5+xr9gZtWVINp0nMh0c0PugRVc8xmCi4FiKLjRI/PDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ae72541ef4ce6b1ebf3117d448b747c2c67a4f2d529bbdf5bffb3e8ed646dad8","last_reissued_at":"2026-05-18T00:11:18.239821Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:11:18.239821Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.03738","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":"2026-05-18T00:11:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Mo9LZZrvqr18tOuAQ2lJGJu5xbpJgsOpKc2lAlglyc9COOdT/JY/JA/gCDc5in+sAI2VynTombR/+XKpspBnCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T10:16:07.900228Z"},"content_sha256":"547cb6e0878548a9f2a84e56a602d3066c6e379b6626925d08f7114c7a11ab7e","schema_version":"1.0","event_id":"sha256:547cb6e0878548a9f2a84e56a602d3066c6e379b6626925d08f7114c7a11ab7e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:VZZFIHXUZZVR5PZRC7KERN2HYL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning Surrogate Models of Document Image Quality Metrics for Automated Document Image Processing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anders Hast, Ekta Vats, Prashant Singh","submitted_at":"2017-12-11T12:13:33Z","abstract_excerpt":"Computation of document image quality metrics often depends upon the availability of a ground truth image corresponding to the document. This limits the applicability of quality metrics in applications such as hyperparameter optimization of image processing algorithms that operate on-the-fly on unseen documents. This work proposes the use of surrogate models to learn the behavior of a given document quality metric on existing datasets where ground truth images are available. The trained surrogate model can later be used to predict the metric value on previously unseen document images without r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.03738","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":"2026-05-18T00:11:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GqSPEJIWvklrBAJ7icHUCLkMLvxcw6u6pOFupTiejdKOJqlbDhsicDzGi+VU5gbncjF1wdrutXWnTIG/M5iLDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T10:16:07.900955Z"},"content_sha256":"7787a133236b4d3995083aa00171061732bbe1540ae1804cf6bb24c6d1e0730d","schema_version":"1.0","event_id":"sha256:7787a133236b4d3995083aa00171061732bbe1540ae1804cf6bb24c6d1e0730d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VZZFIHXUZZVR5PZRC7KERN2HYL/bundle.json","state_url":"https://pith.science/pith/VZZFIHXUZZVR5PZRC7KERN2HYL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VZZFIHXUZZVR5PZRC7KERN2HYL/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":"2026-06-10T10:16:07Z","links":{"resolver":"https://pith.science/pith/VZZFIHXUZZVR5PZRC7KERN2HYL","bundle":"https://pith.science/pith/VZZFIHXUZZVR5PZRC7KERN2HYL/bundle.json","state":"https://pith.science/pith/VZZFIHXUZZVR5PZRC7KERN2HYL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VZZFIHXUZZVR5PZRC7KERN2HYL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:VZZFIHXUZZVR5PZRC7KERN2HYL","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":"123962488a04184187af1afa85c0b55e8dfb220daa1aa84374338bbdf15cd078","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-11T12:13:33Z","title_canon_sha256":"346248d6dc593316043761caf51469bdce958d063adfa4cc7fd3f23fe5450167"},"schema_version":"1.0","source":{"id":"1712.03738","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.03738","created_at":"2026-05-18T00:11:18Z"},{"alias_kind":"arxiv_version","alias_value":"1712.03738v1","created_at":"2026-05-18T00:11:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.03738","created_at":"2026-05-18T00:11:18Z"},{"alias_kind":"pith_short_12","alias_value":"VZZFIHXUZZVR","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VZZFIHXUZZVR5PZR","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VZZFIHXU","created_at":"2026-05-18T12:31:49Z"}],"graph_snapshots":[{"event_id":"sha256:7787a133236b4d3995083aa00171061732bbe1540ae1804cf6bb24c6d1e0730d","target":"graph","created_at":"2026-05-18T00:11:18Z","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":"Computation of document image quality metrics often depends upon the availability of a ground truth image corresponding to the document. This limits the applicability of quality metrics in applications such as hyperparameter optimization of image processing algorithms that operate on-the-fly on unseen documents. This work proposes the use of surrogate models to learn the behavior of a given document quality metric on existing datasets where ground truth images are available. The trained surrogate model can later be used to predict the metric value on previously unseen document images without r","authors_text":"Anders Hast, Ekta Vats, Prashant Singh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-11T12:13:33Z","title":"Learning Surrogate Models of Document Image Quality Metrics for Automated Document Image Processing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.03738","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":"sha256:547cb6e0878548a9f2a84e56a602d3066c6e379b6626925d08f7114c7a11ab7e","target":"record","created_at":"2026-05-18T00:11:18Z","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":"123962488a04184187af1afa85c0b55e8dfb220daa1aa84374338bbdf15cd078","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-12-11T12:13:33Z","title_canon_sha256":"346248d6dc593316043761caf51469bdce958d063adfa4cc7fd3f23fe5450167"},"schema_version":"1.0","source":{"id":"1712.03738","kind":"arxiv","version":1}},"canonical_sha256":"ae72541ef4ce6b1ebf3117d448b747c2c67a4f2d529bbdf5bffb3e8ed646dad8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ae72541ef4ce6b1ebf3117d448b747c2c67a4f2d529bbdf5bffb3e8ed646dad8","first_computed_at":"2026-05-18T00:11:18.239821Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:11:18.239821Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"j78ckcxPHBkfZM6fMYqsnSnl3/Lsk7/T76bxjW+AKdU5+xr9gZtWVINp0nMh0c0PugRVc8xmCi4FiKLjRI/PDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:11:18.240596Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.03738","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:547cb6e0878548a9f2a84e56a602d3066c6e379b6626925d08f7114c7a11ab7e","sha256:7787a133236b4d3995083aa00171061732bbe1540ae1804cf6bb24c6d1e0730d"],"state_sha256":"dfbe439c4037c6f672ebac193c85269ccc4ab77725660088aaef4befaa7bf79c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xjO0ACgrRVSXgBeLzMwTLUATgUvlJcrpK4ibxgD5XpwgGeA5ueVSMyzo1hkEtXk7qGkRSwYjAT+yMcm9AV/MCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T10:16:07.905032Z","bundle_sha256":"a3ac111b6f75e0418f6a487c5a00a45f46dce73bcb484614c8617f6d51959ae5"}}