{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:Y5APGFBCOM2RPWP73WRVWJUY6Q","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":"08c8baec31c0e73dea147e8021cafb29f87b389c38d8c67e6db94636bc79c9cb","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-17T15:54:14Z","title_canon_sha256":"7e735edd0400680a202ffbf34361a9faa99e913b2983918b8f349f985b20eb5f"},"schema_version":"1.0","source":{"id":"2104.08585","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.08585","created_at":"2026-07-05T02:32:53Z"},{"alias_kind":"arxiv_version","alias_value":"2104.08585v1","created_at":"2026-07-05T02:32:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.08585","created_at":"2026-07-05T02:32:53Z"},{"alias_kind":"pith_short_12","alias_value":"Y5APGFBCOM2R","created_at":"2026-07-05T02:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"Y5APGFBCOM2RPWP7","created_at":"2026-07-05T02:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"Y5APGFBC","created_at":"2026-07-05T02:32:53Z"}],"graph_snapshots":[{"event_id":"sha256:3aaf96dc6a252ea92199b74951e89711a65920a5b1467acf80e905b81c4f3b34","target":"graph","created_at":"2026-07-05T02:32:53Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2104.08585/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The Convolutional Neural Network has amazed us with its usage on several applications. Age range estimation using CNN is emerging due to its application in myriad of areas which makes it a state-of-the-art area for research and improve the estimation accuracy. A deep CNN model is used for identification of people's age range in our proposed work. At first, we extracted only face images from image dataset using MTCNN to remove unnecessary features other than face from the image. Secondly, we used random crop technique for data augmentation to improve the model performance. We have used the conc","authors_text":"Ashutosh Chauhan, Dipesh Gyawali, Prashanga Pokharel, Subodh Chandra Shakya","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-17T15:54:14Z","title":"Age Range Estimation using MTCNN and VGG-Face Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.08585","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":"sha256:57b32b59a2a9dec03ff14970b494ffd36f3a872cd850a881b7edc0f104ce2a37","target":"record","created_at":"2026-07-05T02:32:53Z","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":"08c8baec31c0e73dea147e8021cafb29f87b389c38d8c67e6db94636bc79c9cb","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-04-17T15:54:14Z","title_canon_sha256":"7e735edd0400680a202ffbf34361a9faa99e913b2983918b8f349f985b20eb5f"},"schema_version":"1.0","source":{"id":"2104.08585","kind":"arxiv","version":1}},"canonical_sha256":"c740f31422733517d9ffdda35b2698f415f2642fd135843b6f065625aaa02faa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c740f31422733517d9ffdda35b2698f415f2642fd135843b6f065625aaa02faa","first_computed_at":"2026-07-05T02:32:53.826827Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:32:53.826827Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5WHKzsxqFPN+tKG7BiOEcPw6oULvTSx7b+i/TejeFKxEy+E+UTKHmZFPvbNSAfMZGBH0ICh3syIcP37eKGo+CA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:32:53.827285Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.08585","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:57b32b59a2a9dec03ff14970b494ffd36f3a872cd850a881b7edc0f104ce2a37","sha256:3aaf96dc6a252ea92199b74951e89711a65920a5b1467acf80e905b81c4f3b34"],"state_sha256":"b68e7f0a52a3c249a70daacf41f29ef77337d0498ab73d913da928bdd65d0ab1"}