{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:3NZHA2PXT7V5DBS63LPQUI6FKT","short_pith_number":"pith:3NZHA2PX","canonical_record":{"source":{"id":"1808.08993","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-27T18:53:31Z","cross_cats_sorted":[],"title_canon_sha256":"e6178d96dff7ec298f7660f3ee581e031f042ffa8672e7600ee5e332b652e004","abstract_canon_sha256":"a6a3b9b2283c2f22e231fd4de13b0c09ccbe0badfa66b17eeace25775c8cf810"},"schema_version":"1.0"},"canonical_sha256":"db727069f79febd1865edadf0a23c554cade7f08bf7a3e946bf3b55f6e29c44f","source":{"kind":"arxiv","id":"1808.08993","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.08993","created_at":"2026-05-18T00:07:04Z"},{"alias_kind":"arxiv_version","alias_value":"1808.08993v1","created_at":"2026-05-18T00:07:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.08993","created_at":"2026-05-18T00:07:04Z"},{"alias_kind":"pith_short_12","alias_value":"3NZHA2PXT7V5","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"3NZHA2PXT7V5DBS6","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"3NZHA2PX","created_at":"2026-05-18T12:32:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:3NZHA2PXT7V5DBS63LPQUI6FKT","target":"record","payload":{"canonical_record":{"source":{"id":"1808.08993","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-27T18:53:31Z","cross_cats_sorted":[],"title_canon_sha256":"e6178d96dff7ec298f7660f3ee581e031f042ffa8672e7600ee5e332b652e004","abstract_canon_sha256":"a6a3b9b2283c2f22e231fd4de13b0c09ccbe0badfa66b17eeace25775c8cf810"},"schema_version":"1.0"},"canonical_sha256":"db727069f79febd1865edadf0a23c554cade7f08bf7a3e946bf3b55f6e29c44f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:07:04.960720Z","signature_b64":"/Dpod3IKgWwDpU0poJRVFIj/bemReCkUGo5acQD5Pon9KN6Ng34hA/mUWzO0+LMYFSidYUq1LCAbLx7nXSZJAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"db727069f79febd1865edadf0a23c554cade7f08bf7a3e946bf3b55f6e29c44f","last_reissued_at":"2026-05-18T00:07:04.960104Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:07:04.960104Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.08993","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":"2026-05-18T00:07:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F9+msw5jDY1NEE4O6VD0KRqzsiRG+BJsrFIPLam8Y1HTUiQaXHiQoHfX0MY5yW7VBC2WY1euZgDQ/j0Q6HVwCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T20:55:29.457704Z"},"content_sha256":"3ac4ecf490387bc02b63769f04e7226a1009d7745fb444ae074bce0b670baf9e","schema_version":"1.0","event_id":"sha256:3ac4ecf490387bc02b63769f04e7226a1009d7745fb444ae074bce0b670baf9e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:3NZHA2PXT7V5DBS63LPQUI6FKT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Open Set Chinese Character Recognition using Multi-typed Attributes","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Lambert Schomaker, Sheng He","submitted_at":"2018-08-27T18:53:31Z","abstract_excerpt":"Recognition of Off-line Chinese characters is still a challenging problem, especially in historical documents, not only in the number of classes extremely large in comparison to contemporary image retrieval methods, but also new unseen classes can be expected under open learning conditions (even for CNN). Chinese character recognition with zero or a few training samples is a difficult problem and has not been studied yet. In this paper, we propose a new Chinese character recognition method by multi-type attributes, which are based on pronunciation, structure and radicals of Chinese characters,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.08993","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":"2026-05-18T00:07:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"omc16BAzjmodIZy7q+UrKJf225MfVGFK9q2z6fOF2+2wMIhnqJjTi9vXugu/a3NQQaO8gDINJhEVaH2zOgYjAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T20:55:29.458033Z"},"content_sha256":"4cbc9c102d6efcbb213a9144e82b633ac5261bdcbad83dbd003d05bb6ac05ca4","schema_version":"1.0","event_id":"sha256:4cbc9c102d6efcbb213a9144e82b633ac5261bdcbad83dbd003d05bb6ac05ca4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3NZHA2PXT7V5DBS63LPQUI6FKT/bundle.json","state_url":"https://pith.science/pith/3NZHA2PXT7V5DBS63LPQUI6FKT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3NZHA2PXT7V5DBS63LPQUI6FKT/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":"2026-07-06T20:55:29Z","links":{"resolver":"https://pith.science/pith/3NZHA2PXT7V5DBS63LPQUI6FKT","bundle":"https://pith.science/pith/3NZHA2PXT7V5DBS63LPQUI6FKT/bundle.json","state":"https://pith.science/pith/3NZHA2PXT7V5DBS63LPQUI6FKT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3NZHA2PXT7V5DBS63LPQUI6FKT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:3NZHA2PXT7V5DBS63LPQUI6FKT","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":"a6a3b9b2283c2f22e231fd4de13b0c09ccbe0badfa66b17eeace25775c8cf810","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-27T18:53:31Z","title_canon_sha256":"e6178d96dff7ec298f7660f3ee581e031f042ffa8672e7600ee5e332b652e004"},"schema_version":"1.0","source":{"id":"1808.08993","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.08993","created_at":"2026-05-18T00:07:04Z"},{"alias_kind":"arxiv_version","alias_value":"1808.08993v1","created_at":"2026-05-18T00:07:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.08993","created_at":"2026-05-18T00:07:04Z"},{"alias_kind":"pith_short_12","alias_value":"3NZHA2PXT7V5","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_16","alias_value":"3NZHA2PXT7V5DBS6","created_at":"2026-05-18T12:32:02Z"},{"alias_kind":"pith_short_8","alias_value":"3NZHA2PX","created_at":"2026-05-18T12:32:02Z"}],"graph_snapshots":[{"event_id":"sha256:4cbc9c102d6efcbb213a9144e82b633ac5261bdcbad83dbd003d05bb6ac05ca4","target":"graph","created_at":"2026-05-18T00:07:04Z","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":"Recognition of Off-line Chinese characters is still a challenging problem, especially in historical documents, not only in the number of classes extremely large in comparison to contemporary image retrieval methods, but also new unseen classes can be expected under open learning conditions (even for CNN). Chinese character recognition with zero or a few training samples is a difficult problem and has not been studied yet. In this paper, we propose a new Chinese character recognition method by multi-type attributes, which are based on pronunciation, structure and radicals of Chinese characters,","authors_text":"Lambert Schomaker, Sheng He","cross_cats":[],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-27T18:53:31Z","title":"Open Set Chinese Character Recognition using Multi-typed Attributes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.08993","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":"sha256:3ac4ecf490387bc02b63769f04e7226a1009d7745fb444ae074bce0b670baf9e","target":"record","created_at":"2026-05-18T00:07:04Z","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":"a6a3b9b2283c2f22e231fd4de13b0c09ccbe0badfa66b17eeace25775c8cf810","cross_cats_sorted":[],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-27T18:53:31Z","title_canon_sha256":"e6178d96dff7ec298f7660f3ee581e031f042ffa8672e7600ee5e332b652e004"},"schema_version":"1.0","source":{"id":"1808.08993","kind":"arxiv","version":1}},"canonical_sha256":"db727069f79febd1865edadf0a23c554cade7f08bf7a3e946bf3b55f6e29c44f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"db727069f79febd1865edadf0a23c554cade7f08bf7a3e946bf3b55f6e29c44f","first_computed_at":"2026-05-18T00:07:04.960104Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:07:04.960104Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/Dpod3IKgWwDpU0poJRVFIj/bemReCkUGo5acQD5Pon9KN6Ng34hA/mUWzO0+LMYFSidYUq1LCAbLx7nXSZJAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:07:04.960720Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.08993","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3ac4ecf490387bc02b63769f04e7226a1009d7745fb444ae074bce0b670baf9e","sha256:4cbc9c102d6efcbb213a9144e82b633ac5261bdcbad83dbd003d05bb6ac05ca4"],"state_sha256":"5402c9f88c36d9c83792fc45563d3e82a950462268f75bfefb51f217b6852cff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vXHlwa/lrwj0Glg/pC5dOcAuGt9SUP9F/g9L9/pGiDYxy1GyzvAslAlORBNnmyknvaIbWurrmCUYOPB4fiHZAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T20:55:29.459783Z","bundle_sha256":"0fe8cc7a2d662cd39bdd39610bd0d6f989a0fe868cd4f3eab678173e29590233"}}