{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:VPKP6ZHRPVYBYPU7W6ZMLN7TMV","short_pith_number":"pith:VPKP6ZHR","schema_version":"1.0","canonical_sha256":"abd4ff64f17d701c3e9fb7b2c5b7f36565ed0a4bdc5490a7781e23b7e9c20a78","source":{"kind":"arxiv","id":"1902.01522","version":4},"attestation_state":"computed","paper":{"title":"Active Image Synthesis for Efficient Labeling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ben Wang, Chuck Zhang, Jialei Chen, Kan Wang, Mani A. Vannan, Yujia Xie, Zhen Qian","submitted_at":"2019-02-05T02:49:09Z","abstract_excerpt":"The great success achieved by deep neural networks attracts increasing attention from the manufacturing and healthcare communities. However, the limited availability of data and high costs of data collection are the major challenges for the applications in those fields. We propose in this work AISEL, an active image synthesis method for efficient labeling to improve the performance of the small-data learning tasks. Specifically, a complementary AISEL dataset is generated, with labels actively acquired via a physics-based method to incorporate underlining physical knowledge at hand. An importan"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1902.01522","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-02-05T02:49:09Z","cross_cats_sorted":[],"title_canon_sha256":"1b3f9ee1fae90e7da118d101442df28b310ff45293bd7512699c1a9dc5a6f82d","abstract_canon_sha256":"e88cbd45cc039196635cf7bdb06bc3c92fec35d55f96a92afacf6d73e3ef4afc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:40:25.012861Z","signature_b64":"94roxKJNVUGL169ZevpQAXEG9cmsfb1PKlr9XCOw+3BIDAw39QcN1vpnGHrYX58ZRm6QiAF7Aavhd88872ewCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"abd4ff64f17d701c3e9fb7b2c5b7f36565ed0a4bdc5490a7781e23b7e9c20a78","last_reissued_at":"2026-07-05T02:40:25.012465Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:40:25.012465Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Active Image Synthesis for Efficient Labeling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ben Wang, Chuck Zhang, Jialei Chen, Kan Wang, Mani A. Vannan, Yujia Xie, Zhen Qian","submitted_at":"2019-02-05T02:49:09Z","abstract_excerpt":"The great success achieved by deep neural networks attracts increasing attention from the manufacturing and healthcare communities. However, the limited availability of data and high costs of data collection are the major challenges for the applications in those fields. We propose in this work AISEL, an active image synthesis method for efficient labeling to improve the performance of the small-data learning tasks. Specifically, a complementary AISEL dataset is generated, with labels actively acquired via a physics-based method to incorporate underlining physical knowledge at hand. An importan"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.01522","kind":"arxiv","version":4},"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/1902.01522/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1902.01522","created_at":"2026-07-05T02:40:25.012530+00:00"},{"alias_kind":"arxiv_version","alias_value":"1902.01522v4","created_at":"2026-07-05T02:40:25.012530+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.01522","created_at":"2026-07-05T02:40:25.012530+00:00"},{"alias_kind":"pith_short_12","alias_value":"VPKP6ZHRPVYB","created_at":"2026-07-05T02:40:25.012530+00:00"},{"alias_kind":"pith_short_16","alias_value":"VPKP6ZHRPVYBYPU7","created_at":"2026-07-05T02:40:25.012530+00:00"},{"alias_kind":"pith_short_8","alias_value":"VPKP6ZHR","created_at":"2026-07-05T02:40:25.012530+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VPKP6ZHRPVYBYPU7W6ZMLN7TMV","json":"https://pith.science/pith/VPKP6ZHRPVYBYPU7W6ZMLN7TMV.json","graph_json":"https://pith.science/api/pith-number/VPKP6ZHRPVYBYPU7W6ZMLN7TMV/graph.json","events_json":"https://pith.science/api/pith-number/VPKP6ZHRPVYBYPU7W6ZMLN7TMV/events.json","paper":"https://pith.science/paper/VPKP6ZHR"},"agent_actions":{"view_html":"https://pith.science/pith/VPKP6ZHRPVYBYPU7W6ZMLN7TMV","download_json":"https://pith.science/pith/VPKP6ZHRPVYBYPU7W6ZMLN7TMV.json","view_paper":"https://pith.science/paper/VPKP6ZHR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1902.01522&json=true","fetch_graph":"https://pith.science/api/pith-number/VPKP6ZHRPVYBYPU7W6ZMLN7TMV/graph.json","fetch_events":"https://pith.science/api/pith-number/VPKP6ZHRPVYBYPU7W6ZMLN7TMV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VPKP6ZHRPVYBYPU7W6ZMLN7TMV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VPKP6ZHRPVYBYPU7W6ZMLN7TMV/action/storage_attestation","attest_author":"https://pith.science/pith/VPKP6ZHRPVYBYPU7W6ZMLN7TMV/action/author_attestation","sign_citation":"https://pith.science/pith/VPKP6ZHRPVYBYPU7W6ZMLN7TMV/action/citation_signature","submit_replication":"https://pith.science/pith/VPKP6ZHRPVYBYPU7W6ZMLN7TMV/action/replication_record"}},"created_at":"2026-07-05T02:40:25.012530+00:00","updated_at":"2026-07-05T02:40:25.012530+00:00"}