{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:52LREONVG4E4IPZVVDV5HEPP5W","short_pith_number":"pith:52LREONV","canonical_record":{"source":{"id":"1703.00586","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-03-02T02:15:05Z","cross_cats_sorted":[],"title_canon_sha256":"860120181064d58e6ee3a0e82ca1280ac83e7508d720e1c610d37d35eabe3804","abstract_canon_sha256":"f7a3e1afff4641d8178fb2f2450b64fb53a2f1fdc1120f2174604d6e5d040092"},"schema_version":"1.0"},"canonical_sha256":"ee971239b53709c43f35a8ebd391efeda1e8efecc2d275d1fd1a9937c6eddb17","source":{"kind":"arxiv","id":"1703.00586","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.00586","created_at":"2026-05-18T00:43:08Z"},{"alias_kind":"arxiv_version","alias_value":"1703.00586v2","created_at":"2026-05-18T00:43:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.00586","created_at":"2026-05-18T00:43:08Z"},{"alias_kind":"pith_short_12","alias_value":"52LREONVG4E4","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_16","alias_value":"52LREONVG4E4IPZV","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_8","alias_value":"52LREONV","created_at":"2026-05-18T12:31:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:52LREONVG4E4IPZVVDV5HEPP5W","target":"record","payload":{"canonical_record":{"source":{"id":"1703.00586","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-03-02T02:15:05Z","cross_cats_sorted":[],"title_canon_sha256":"860120181064d58e6ee3a0e82ca1280ac83e7508d720e1c610d37d35eabe3804","abstract_canon_sha256":"f7a3e1afff4641d8178fb2f2450b64fb53a2f1fdc1120f2174604d6e5d040092"},"schema_version":"1.0"},"canonical_sha256":"ee971239b53709c43f35a8ebd391efeda1e8efecc2d275d1fd1a9937c6eddb17","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:43:08.586946Z","signature_b64":"bViULIHEB5uWVCCmeUSTWb6Yb/HS4osXj6eLYNBHgxMI9ymOjPiSCnr7GCPv3XS4K86YvVC4nGRRlBFA6c5iAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee971239b53709c43f35a8ebd391efeda1e8efecc2d275d1fd1a9937c6eddb17","last_reissued_at":"2026-05-18T00:43:08.585980Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:43:08.585980Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.00586","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":"2026-05-18T00:43:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aXYvHObAADAyvrL+eeZhx4oYZ6xo+UI8xOwAzBFrnThC9fD+eAJPw7ClRD4BXlkbiMRy/Jr+ZWqwVh29F6DQAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T04:13:43.353222Z"},"content_sha256":"47841ce939ff12fa5c8e90533f8b2bed7c79a520e31200916876f37ec288f203","schema_version":"1.0","event_id":"sha256:47841ce939ff12fa5c8e90533f8b2bed7c79a520e31200916876f37ec288f203"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:52LREONVG4E4IPZVVDV5HEPP5W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A novel image tag completion method based on convolutional neural network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Gaoyuan Liang, Guohui Zhang, Jingbin Wang, Jing-Yan Wang, Nitin Patil, Ru-Ze Liang, Weizhi Li, Yanbin Wu, Yanyan Geng, Yi Gu","submitted_at":"2017-03-02T02:15:05Z","abstract_excerpt":"In the problems of image retrieval and annotation, complete textual tag lists of images play critical roles. However, in real-world applications, the image tags are usually incomplete, thus it is important to learn the complete tags for images. In this paper, we study the problem of image tag complete and proposed a novel method for this problem based on a popular image representation method, convolutional neural network (CNN). The method estimates the complete tags from the convolutional filtering outputs of images based on a linear predictor. The CNN parameters, linear predictor, and the com"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.00586","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":""},"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":"2026-05-18T00:43:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C23BsVEVs2sdaSukxFmqNvA3wVWk/Dd9Ms1LeOEgbA+HeT/NAi3qkJm0jca5E5F7gEbnXhogX2OpTcbrDklYBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T04:13:43.353879Z"},"content_sha256":"259e165e7b81ce80fcaeb8154d1bb1fd2b48aec3693b5b05f2c6ce2937fb6bc8","schema_version":"1.0","event_id":"sha256:259e165e7b81ce80fcaeb8154d1bb1fd2b48aec3693b5b05f2c6ce2937fb6bc8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/52LREONVG4E4IPZVVDV5HEPP5W/bundle.json","state_url":"https://pith.science/pith/52LREONVG4E4IPZVVDV5HEPP5W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/52LREONVG4E4IPZVVDV5HEPP5W/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":"2026-05-30T04:13:43Z","links":{"resolver":"https://pith.science/pith/52LREONVG4E4IPZVVDV5HEPP5W","bundle":"https://pith.science/pith/52LREONVG4E4IPZVVDV5HEPP5W/bundle.json","state":"https://pith.science/pith/52LREONVG4E4IPZVVDV5HEPP5W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/52LREONVG4E4IPZVVDV5HEPP5W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:52LREONVG4E4IPZVVDV5HEPP5W","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":"f7a3e1afff4641d8178fb2f2450b64fb53a2f1fdc1120f2174604d6e5d040092","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-03-02T02:15:05Z","title_canon_sha256":"860120181064d58e6ee3a0e82ca1280ac83e7508d720e1c610d37d35eabe3804"},"schema_version":"1.0","source":{"id":"1703.00586","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.00586","created_at":"2026-05-18T00:43:08Z"},{"alias_kind":"arxiv_version","alias_value":"1703.00586v2","created_at":"2026-05-18T00:43:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.00586","created_at":"2026-05-18T00:43:08Z"},{"alias_kind":"pith_short_12","alias_value":"52LREONVG4E4","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_16","alias_value":"52LREONVG4E4IPZV","created_at":"2026-05-18T12:31:00Z"},{"alias_kind":"pith_short_8","alias_value":"52LREONV","created_at":"2026-05-18T12:31:00Z"}],"graph_snapshots":[{"event_id":"sha256:259e165e7b81ce80fcaeb8154d1bb1fd2b48aec3693b5b05f2c6ce2937fb6bc8","target":"graph","created_at":"2026-05-18T00:43:08Z","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 the problems of image retrieval and annotation, complete textual tag lists of images play critical roles. However, in real-world applications, the image tags are usually incomplete, thus it is important to learn the complete tags for images. In this paper, we study the problem of image tag complete and proposed a novel method for this problem based on a popular image representation method, convolutional neural network (CNN). The method estimates the complete tags from the convolutional filtering outputs of images based on a linear predictor. The CNN parameters, linear predictor, and the com","authors_text":"Gaoyuan Liang, Guohui Zhang, Jingbin Wang, Jing-Yan Wang, Nitin Patil, Ru-Ze Liang, Weizhi Li, Yanbin Wu, Yanyan Geng, Yi Gu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-03-02T02:15:05Z","title":"A novel image tag completion method based on convolutional neural network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.00586","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":"sha256:47841ce939ff12fa5c8e90533f8b2bed7c79a520e31200916876f37ec288f203","target":"record","created_at":"2026-05-18T00:43:08Z","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":"f7a3e1afff4641d8178fb2f2450b64fb53a2f1fdc1120f2174604d6e5d040092","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-03-02T02:15:05Z","title_canon_sha256":"860120181064d58e6ee3a0e82ca1280ac83e7508d720e1c610d37d35eabe3804"},"schema_version":"1.0","source":{"id":"1703.00586","kind":"arxiv","version":2}},"canonical_sha256":"ee971239b53709c43f35a8ebd391efeda1e8efecc2d275d1fd1a9937c6eddb17","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ee971239b53709c43f35a8ebd391efeda1e8efecc2d275d1fd1a9937c6eddb17","first_computed_at":"2026-05-18T00:43:08.585980Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:43:08.585980Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bViULIHEB5uWVCCmeUSTWb6Yb/HS4osXj6eLYNBHgxMI9ymOjPiSCnr7GCPv3XS4K86YvVC4nGRRlBFA6c5iAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:43:08.586946Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.00586","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:47841ce939ff12fa5c8e90533f8b2bed7c79a520e31200916876f37ec288f203","sha256:259e165e7b81ce80fcaeb8154d1bb1fd2b48aec3693b5b05f2c6ce2937fb6bc8"],"state_sha256":"c1f1380a033b6dc70de1145e6e70adb1747ba7097c061717a44e265118699f1e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pZTWj81Utx3rJ+mQEpnLrG7WROADJp85pKLc1l/y2/od7sZJn3hkw27GkF95DJAD+C9GpM1qkeIdl4jdbN0gCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T04:13:43.356519Z","bundle_sha256":"c6e7f464260dad3e9c0748d5c60158da19302d69d33669d38f0c3041ced717b1"}}