{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:4DAAIFUYGWZI7P7EVV4K2BSIW7","short_pith_number":"pith:4DAAIFUY","canonical_record":{"source":{"id":"1901.04420","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-14T17:30:46Z","cross_cats_sorted":["eess.IV","stat.ML"],"title_canon_sha256":"7e9eea6cc5b48bc3aabe0d1da6b5afe95d4845f906f3c1df504ed4e5414795bf","abstract_canon_sha256":"1ceac6a67d7c57132383390babe5a7a83f61df473652013bc57c6c99257f38df"},"schema_version":"1.0"},"canonical_sha256":"e0c004169835b28fbfe4ad78ad0648b7f5f1423b98dde9eb4d3b6006d441dc4b","source":{"kind":"arxiv","id":"1901.04420","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.04420","created_at":"2026-05-17T23:56:25Z"},{"alias_kind":"arxiv_version","alias_value":"1901.04420v1","created_at":"2026-05-17T23:56:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.04420","created_at":"2026-05-17T23:56:25Z"},{"alias_kind":"pith_short_12","alias_value":"4DAAIFUYGWZI","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4DAAIFUYGWZI7P7E","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4DAAIFUY","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:4DAAIFUYGWZI7P7EVV4K2BSIW7","target":"record","payload":{"canonical_record":{"source":{"id":"1901.04420","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-14T17:30:46Z","cross_cats_sorted":["eess.IV","stat.ML"],"title_canon_sha256":"7e9eea6cc5b48bc3aabe0d1da6b5afe95d4845f906f3c1df504ed4e5414795bf","abstract_canon_sha256":"1ceac6a67d7c57132383390babe5a7a83f61df473652013bc57c6c99257f38df"},"schema_version":"1.0"},"canonical_sha256":"e0c004169835b28fbfe4ad78ad0648b7f5f1423b98dde9eb4d3b6006d441dc4b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:56:25.616791Z","signature_b64":"8OeCOmBsDjVdAvb2zECuDXQTL1zIwiLghruFnsBZ2P0397RFd3XxVS+Sa5Pn84NJ/U9X2Q+wBqEEpnMjn0WdBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e0c004169835b28fbfe4ad78ad0648b7f5f1423b98dde9eb4d3b6006d441dc4b","last_reissued_at":"2026-05-17T23:56:25.616271Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:56:25.616271Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.04420","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":"2026-05-17T23:56:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6zMxlPHbZLCb0tXh+ZUzqWS+Hpyd/rG+ZfAaDzJinUTNiOnp6/AbuhNNptN5whK3P6tsGSnIzt4vDP9B27S6Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T07:17:40.095608Z"},"content_sha256":"4a0fd849f70e3988221b3dc5079ac39dd85f27f10c128c33de168893ca2d9dd0","schema_version":"1.0","event_id":"sha256:4a0fd849f70e3988221b3dc5079ac39dd85f27f10c128c33de168893ca2d9dd0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:4DAAIFUYGWZI7P7EVV4K2BSIW7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Data Augmentation with Manifold Exploring Geometric Transformations for Increased Performance and Robustness","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV","stat.ML"],"primary_cat":"cs.LG","authors_text":"Abhijit Guha Roy, Christian Wachinger, Magdalini Paschali, Muhammad Ferjad Naeem, Nassir Navab, R\\\"udiger G\\\"obl, Walter Simson","submitted_at":"2019-01-14T17:30:46Z","abstract_excerpt":"In this paper we propose a novel augmentation technique that improves not only the performance of deep neural networks on clean test data, but also significantly increases their robustness to random transformations, both affine and projective. Inspired by ManiFool, the augmentation is performed by a line-search manifold-exploration method that learns affine geometric transformations that lead to the misclassification on an image, while ensuring that it remains on the same manifold as the training data.\n  This augmentation method populates any training dataset with images that lie on the border"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.04420","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":"2026-05-17T23:56:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bBKPrJs84TrBDl3+JCpWFvc3K3tIdEMXEKLrI+PuJp0plsUU0w2iLQEf4XjbxjxWujRGKxTmke7rYG2Cip7rAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T07:17:40.096035Z"},"content_sha256":"fc6a95fe92a7195267b2e0b7b5a8480cef73f377c39583ee536b9b52ffbf72be","schema_version":"1.0","event_id":"sha256:fc6a95fe92a7195267b2e0b7b5a8480cef73f377c39583ee536b9b52ffbf72be"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4DAAIFUYGWZI7P7EVV4K2BSIW7/bundle.json","state_url":"https://pith.science/pith/4DAAIFUYGWZI7P7EVV4K2BSIW7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4DAAIFUYGWZI7P7EVV4K2BSIW7/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":"2026-05-31T07:17:40Z","links":{"resolver":"https://pith.science/pith/4DAAIFUYGWZI7P7EVV4K2BSIW7","bundle":"https://pith.science/pith/4DAAIFUYGWZI7P7EVV4K2BSIW7/bundle.json","state":"https://pith.science/pith/4DAAIFUYGWZI7P7EVV4K2BSIW7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4DAAIFUYGWZI7P7EVV4K2BSIW7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:4DAAIFUYGWZI7P7EVV4K2BSIW7","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":"1ceac6a67d7c57132383390babe5a7a83f61df473652013bc57c6c99257f38df","cross_cats_sorted":["eess.IV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-14T17:30:46Z","title_canon_sha256":"7e9eea6cc5b48bc3aabe0d1da6b5afe95d4845f906f3c1df504ed4e5414795bf"},"schema_version":"1.0","source":{"id":"1901.04420","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.04420","created_at":"2026-05-17T23:56:25Z"},{"alias_kind":"arxiv_version","alias_value":"1901.04420v1","created_at":"2026-05-17T23:56:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.04420","created_at":"2026-05-17T23:56:25Z"},{"alias_kind":"pith_short_12","alias_value":"4DAAIFUYGWZI","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4DAAIFUYGWZI7P7E","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4DAAIFUY","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:fc6a95fe92a7195267b2e0b7b5a8480cef73f377c39583ee536b9b52ffbf72be","target":"graph","created_at":"2026-05-17T23:56:25Z","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":"In this paper we propose a novel augmentation technique that improves not only the performance of deep neural networks on clean test data, but also significantly increases their robustness to random transformations, both affine and projective. Inspired by ManiFool, the augmentation is performed by a line-search manifold-exploration method that learns affine geometric transformations that lead to the misclassification on an image, while ensuring that it remains on the same manifold as the training data.\n  This augmentation method populates any training dataset with images that lie on the border","authors_text":"Abhijit Guha Roy, Christian Wachinger, Magdalini Paschali, Muhammad Ferjad Naeem, Nassir Navab, R\\\"udiger G\\\"obl, Walter Simson","cross_cats":["eess.IV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-14T17:30:46Z","title":"Data Augmentation with Manifold Exploring Geometric Transformations for Increased Performance and Robustness"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.04420","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":"sha256:4a0fd849f70e3988221b3dc5079ac39dd85f27f10c128c33de168893ca2d9dd0","target":"record","created_at":"2026-05-17T23:56:25Z","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":"1ceac6a67d7c57132383390babe5a7a83f61df473652013bc57c6c99257f38df","cross_cats_sorted":["eess.IV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-01-14T17:30:46Z","title_canon_sha256":"7e9eea6cc5b48bc3aabe0d1da6b5afe95d4845f906f3c1df504ed4e5414795bf"},"schema_version":"1.0","source":{"id":"1901.04420","kind":"arxiv","version":1}},"canonical_sha256":"e0c004169835b28fbfe4ad78ad0648b7f5f1423b98dde9eb4d3b6006d441dc4b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e0c004169835b28fbfe4ad78ad0648b7f5f1423b98dde9eb4d3b6006d441dc4b","first_computed_at":"2026-05-17T23:56:25.616271Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:56:25.616271Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8OeCOmBsDjVdAvb2zECuDXQTL1zIwiLghruFnsBZ2P0397RFd3XxVS+Sa5Pn84NJ/U9X2Q+wBqEEpnMjn0WdBw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:56:25.616791Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.04420","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4a0fd849f70e3988221b3dc5079ac39dd85f27f10c128c33de168893ca2d9dd0","sha256:fc6a95fe92a7195267b2e0b7b5a8480cef73f377c39583ee536b9b52ffbf72be"],"state_sha256":"33dfeb06a7f7f83817941e4c5e879d35640a4021cf9fdf6f9bf0fd5b93a2c739"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Jrh+kI+Eae+g60tUfnplaKqlzkbVnETtaG+vZDdcolr+YoQk+X0IhQ9w+HhE1/mGXpHD5VYjGMNJ277kwPrPBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T07:17:40.098935Z","bundle_sha256":"10f22ee0509fa5ae51defc6337cc262052fb046e5fc0f57af6b6d0673aefa9ac"}}