{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:VRVVB3MWWFS3HT5WGSBEH7FREN","short_pith_number":"pith:VRVVB3MW","schema_version":"1.0","canonical_sha256":"ac6b50ed96b165b3cfb6348243fcb123483d0216c37c2b9bfaa9755a27ec5e29","source":{"kind":"arxiv","id":"1807.10421","version":1},"attestation_state":"computed","paper":{"title":"Fusion Network for Face-based Age Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chang-Tsun Li, Haoyi Wang, Victor Sanchez, Xingjie Wei","submitted_at":"2018-07-27T03:22:10Z","abstract_excerpt":"Convolutional Neural Networks (CNN) have been applied to age-related research as the core framework. Although faces are composed of numerous facial attributes, most works with CNNs still consider a face as a typical object and do not pay enough attention to facial regions that carry age-specific feature for this particular task. In this paper, we propose a novel CNN architecture called Fusion Network (FusionNet) to tackle the age estimation problem. Apart from the whole face image, the FusionNet successively takes several age-specific facial patches as part of the input to emphasize the age-sp"},"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":"1807.10421","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-27T03:22:10Z","cross_cats_sorted":[],"title_canon_sha256":"da631b7785c694562137f6bc0c1e1c5e838e7ffc66032052c55f03bca98b222d","abstract_canon_sha256":"3d3ade04c767d30e71ff0fcb008fef4f66d9eb40302cc6bf7dd44657d6238f37"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:40.683564Z","signature_b64":"6yoW/HpXmpSeWt4F0cN6zAr+1w4fXZ4Xsz0ScyEVGZzJh/jxCf8l6aui2623/56VxQSuIZYhuy0wJycIh2VkBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac6b50ed96b165b3cfb6348243fcb123483d0216c37c2b9bfaa9755a27ec5e29","last_reissued_at":"2026-05-18T00:09:40.682987Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:40.682987Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fusion Network for Face-based Age Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chang-Tsun Li, Haoyi Wang, Victor Sanchez, Xingjie Wei","submitted_at":"2018-07-27T03:22:10Z","abstract_excerpt":"Convolutional Neural Networks (CNN) have been applied to age-related research as the core framework. Although faces are composed of numerous facial attributes, most works with CNNs still consider a face as a typical object and do not pay enough attention to facial regions that carry age-specific feature for this particular task. In this paper, we propose a novel CNN architecture called Fusion Network (FusionNet) to tackle the age estimation problem. Apart from the whole face image, the FusionNet successively takes several age-specific facial patches as part of the input to emphasize the age-sp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.10421","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1807.10421","created_at":"2026-05-18T00:09:40.683079+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.10421v1","created_at":"2026-05-18T00:09:40.683079+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.10421","created_at":"2026-05-18T00:09:40.683079+00:00"},{"alias_kind":"pith_short_12","alias_value":"VRVVB3MWWFS3","created_at":"2026-05-18T12:32:59.047623+00:00"},{"alias_kind":"pith_short_16","alias_value":"VRVVB3MWWFS3HT5W","created_at":"2026-05-18T12:32:59.047623+00:00"},{"alias_kind":"pith_short_8","alias_value":"VRVVB3MW","created_at":"2026-05-18T12:32:59.047623+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/VRVVB3MWWFS3HT5WGSBEH7FREN","json":"https://pith.science/pith/VRVVB3MWWFS3HT5WGSBEH7FREN.json","graph_json":"https://pith.science/api/pith-number/VRVVB3MWWFS3HT5WGSBEH7FREN/graph.json","events_json":"https://pith.science/api/pith-number/VRVVB3MWWFS3HT5WGSBEH7FREN/events.json","paper":"https://pith.science/paper/VRVVB3MW"},"agent_actions":{"view_html":"https://pith.science/pith/VRVVB3MWWFS3HT5WGSBEH7FREN","download_json":"https://pith.science/pith/VRVVB3MWWFS3HT5WGSBEH7FREN.json","view_paper":"https://pith.science/paper/VRVVB3MW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.10421&json=true","fetch_graph":"https://pith.science/api/pith-number/VRVVB3MWWFS3HT5WGSBEH7FREN/graph.json","fetch_events":"https://pith.science/api/pith-number/VRVVB3MWWFS3HT5WGSBEH7FREN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VRVVB3MWWFS3HT5WGSBEH7FREN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VRVVB3MWWFS3HT5WGSBEH7FREN/action/storage_attestation","attest_author":"https://pith.science/pith/VRVVB3MWWFS3HT5WGSBEH7FREN/action/author_attestation","sign_citation":"https://pith.science/pith/VRVVB3MWWFS3HT5WGSBEH7FREN/action/citation_signature","submit_replication":"https://pith.science/pith/VRVVB3MWWFS3HT5WGSBEH7FREN/action/replication_record"}},"created_at":"2026-05-18T00:09:40.683079+00:00","updated_at":"2026-05-18T00:09:40.683079+00:00"}