{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:XFXO6IHQIATSAD37I7W6EDNLIY","short_pith_number":"pith:XFXO6IHQ","canonical_record":{"source":{"id":"2212.10054","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-12-20T08:01:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b89cef7b320365846e1051ff40325d84f7a84275a16f45b281ff5670f15c9ab0","abstract_canon_sha256":"cc8fa33b6bf6731cce12b960bdf04c4af1701c7c4f3bdbf6a0d02c732063bbc6"},"schema_version":"1.0"},"canonical_sha256":"b96eef20f04027200f7f47ede20dab463ffcc63864c6060e8a758ae6103f4d56","source":{"kind":"arxiv","id":"2212.10054","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.10054","created_at":"2026-07-05T05:27:49Z"},{"alias_kind":"arxiv_version","alias_value":"2212.10054v2","created_at":"2026-07-05T05:27:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.10054","created_at":"2026-07-05T05:27:49Z"},{"alias_kind":"pith_short_12","alias_value":"XFXO6IHQIATS","created_at":"2026-07-05T05:27:49Z"},{"alias_kind":"pith_short_16","alias_value":"XFXO6IHQIATSAD37","created_at":"2026-07-05T05:27:49Z"},{"alias_kind":"pith_short_8","alias_value":"XFXO6IHQ","created_at":"2026-07-05T05:27:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:XFXO6IHQIATSAD37I7W6EDNLIY","target":"record","payload":{"canonical_record":{"source":{"id":"2212.10054","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-12-20T08:01:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"b89cef7b320365846e1051ff40325d84f7a84275a16f45b281ff5670f15c9ab0","abstract_canon_sha256":"cc8fa33b6bf6731cce12b960bdf04c4af1701c7c4f3bdbf6a0d02c732063bbc6"},"schema_version":"1.0"},"canonical_sha256":"b96eef20f04027200f7f47ede20dab463ffcc63864c6060e8a758ae6103f4d56","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:27:49.982376Z","signature_b64":"zq8Ql/VopHjIM3/kMAk3gbbVK4IkcihF6CXDHEJ7jTetZY7DGMqVBonrFyavUoMf6IvWjo4qLNJGq00PcPWmBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b96eef20f04027200f7f47ede20dab463ffcc63864c6060e8a758ae6103f4d56","last_reissued_at":"2026-07-05T05:27:49.981960Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:27:49.981960Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.10054","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":"2026-07-05T05:27:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YxvQ8ukdRTSt2i7Adi8eA8V+p1Te80WY7qFI1RL/CHrZlVmZvlMvOacb3ACxSIdzcD8V+0wKgqSvJruhtye1Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:12:04.303524Z"},"content_sha256":"2245ab5e0f8c358a1c2feea951fc35d7a7bfae5dbc1aa853f1adf4cc655ee72b","schema_version":"1.0","event_id":"sha256:2245ab5e0f8c358a1c2feea951fc35d7a7bfae5dbc1aa853f1adf4cc655ee72b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:XFXO6IHQIATSAD37I7W6EDNLIY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"VoronoiPatches: Evaluating A New Data Augmentation Method","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Claudia Linnhoff-Popien, Gretchen Griffin, Jonas N\\\"u{\\ss}lein, Maximilian Zorn, Michael K\\\"olle, Steffen Illium","submitted_at":"2022-12-20T08:01:03Z","abstract_excerpt":"Overfitting is a problem in Convolutional Neural Networks (CNN) that causes poor generalization of models on unseen data. To remediate this problem, many new and diverse data augmentation methods (DA) have been proposed to supplement or generate more training data, and thereby increase its quality. In this work, we propose a new data augmentation algorithm: VoronoiPatches (VP). We primarily utilize non-linear recombination of information within an image, fragmenting and occluding small information patches. Unlike other DA methods, VP uses small convex polygon-shaped patches in a random layout "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.10054","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2212.10054/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":"2026-07-05T05:27:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BrzRas46mFU+65b8f3p4xehT/z1V61CGT1fWkv6+MizIC1LqIhG8R9uJW8eC3TUDilxhtWEIsxlXEYZ28d/eDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:12:04.304033Z"},"content_sha256":"aac867ae09248ef271911a433bf80db0eb9ca56251d7c496f82915f710d20ac9","schema_version":"1.0","event_id":"sha256:aac867ae09248ef271911a433bf80db0eb9ca56251d7c496f82915f710d20ac9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XFXO6IHQIATSAD37I7W6EDNLIY/bundle.json","state_url":"https://pith.science/pith/XFXO6IHQIATSAD37I7W6EDNLIY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XFXO6IHQIATSAD37I7W6EDNLIY/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":"2026-08-04T15:12:04Z","links":{"resolver":"https://pith.science/pith/XFXO6IHQIATSAD37I7W6EDNLIY","bundle":"https://pith.science/pith/XFXO6IHQIATSAD37I7W6EDNLIY/bundle.json","state":"https://pith.science/pith/XFXO6IHQIATSAD37I7W6EDNLIY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XFXO6IHQIATSAD37I7W6EDNLIY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:XFXO6IHQIATSAD37I7W6EDNLIY","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":"cc8fa33b6bf6731cce12b960bdf04c4af1701c7c4f3bdbf6a0d02c732063bbc6","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-12-20T08:01:03Z","title_canon_sha256":"b89cef7b320365846e1051ff40325d84f7a84275a16f45b281ff5670f15c9ab0"},"schema_version":"1.0","source":{"id":"2212.10054","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.10054","created_at":"2026-07-05T05:27:49Z"},{"alias_kind":"arxiv_version","alias_value":"2212.10054v2","created_at":"2026-07-05T05:27:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.10054","created_at":"2026-07-05T05:27:49Z"},{"alias_kind":"pith_short_12","alias_value":"XFXO6IHQIATS","created_at":"2026-07-05T05:27:49Z"},{"alias_kind":"pith_short_16","alias_value":"XFXO6IHQIATSAD37","created_at":"2026-07-05T05:27:49Z"},{"alias_kind":"pith_short_8","alias_value":"XFXO6IHQ","created_at":"2026-07-05T05:27:49Z"}],"graph_snapshots":[{"event_id":"sha256:aac867ae09248ef271911a433bf80db0eb9ca56251d7c496f82915f710d20ac9","target":"graph","created_at":"2026-07-05T05:27:49Z","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/2212.10054/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Overfitting is a problem in Convolutional Neural Networks (CNN) that causes poor generalization of models on unseen data. To remediate this problem, many new and diverse data augmentation methods (DA) have been proposed to supplement or generate more training data, and thereby increase its quality. In this work, we propose a new data augmentation algorithm: VoronoiPatches (VP). We primarily utilize non-linear recombination of information within an image, fragmenting and occluding small information patches. Unlike other DA methods, VP uses small convex polygon-shaped patches in a random layout ","authors_text":"Claudia Linnhoff-Popien, Gretchen Griffin, Jonas N\\\"u{\\ss}lein, Maximilian Zorn, Michael K\\\"olle, Steffen Illium","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-12-20T08:01:03Z","title":"VoronoiPatches: Evaluating A New Data Augmentation Method"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.10054","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":"sha256:2245ab5e0f8c358a1c2feea951fc35d7a7bfae5dbc1aa853f1adf4cc655ee72b","target":"record","created_at":"2026-07-05T05:27:49Z","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":"cc8fa33b6bf6731cce12b960bdf04c4af1701c7c4f3bdbf6a0d02c732063bbc6","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-12-20T08:01:03Z","title_canon_sha256":"b89cef7b320365846e1051ff40325d84f7a84275a16f45b281ff5670f15c9ab0"},"schema_version":"1.0","source":{"id":"2212.10054","kind":"arxiv","version":2}},"canonical_sha256":"b96eef20f04027200f7f47ede20dab463ffcc63864c6060e8a758ae6103f4d56","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b96eef20f04027200f7f47ede20dab463ffcc63864c6060e8a758ae6103f4d56","first_computed_at":"2026-07-05T05:27:49.981960Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:27:49.981960Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zq8Ql/VopHjIM3/kMAk3gbbVK4IkcihF6CXDHEJ7jTetZY7DGMqVBonrFyavUoMf6IvWjo4qLNJGq00PcPWmBw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:27:49.982376Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.10054","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2245ab5e0f8c358a1c2feea951fc35d7a7bfae5dbc1aa853f1adf4cc655ee72b","sha256:aac867ae09248ef271911a433bf80db0eb9ca56251d7c496f82915f710d20ac9"],"state_sha256":"4623fe0937181ed6a76a81bf20e7015ad094d9e1c24ce46d96ffb602701120bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"adVW7rB4R+mM3YeQKawhaG+OYXpGorEAPNFuBmHVF3yh/af7nMP7iWZE34WCOAdTOypAOeCYkHYT1dYSkanYCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T15:12:04.307887Z","bundle_sha256":"fb8fa6e629853f46308abdd12cdebd91c7a997c64fd5dfb68e8480d3a2ed815b"}}