{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:5R6LULEQKEDVAZBFUQMWYAIKCG","short_pith_number":"pith:5R6LULEQ","schema_version":"1.0","canonical_sha256":"ec7cba2c905107506425a4196c010a1186abbeb765228fcaf549847ffb02e47b","source":{"kind":"arxiv","id":"1809.10432","version":1},"attestation_state":"computed","paper":{"title":"CNN Based Posture-Free Hand Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Richard Adiguna, Yustinus Eko Soelistio","submitted_at":"2018-09-27T10:00:31Z","abstract_excerpt":"Although many studies suggest high performance hand detection methods, those methods are likely to be overfitting. Fortunately, the Convolution Neural Network (CNN) based approach provides a better way that is less sensitive to translation and hand poses. However the CNN approach is complex and can increase computational time, which at the end reduce its effectiveness on a system where the speed is essential.In this study we propose a shallow CNN network which is fast, and insensitive to translation and hand poses. It is tested on two different domains of hand datasets, and performs in relativ"},"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":"1809.10432","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-27T10:00:31Z","cross_cats_sorted":[],"title_canon_sha256":"9dd0ec169dfad60ac3d95436b81575a14c4bef45c5379cca521038570adacea1","abstract_canon_sha256":"37cd335033c53bdeeddb6cb9ecbf4cbec9be78b8fb648277eaa52a1ea3d7dbfc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:38.363419Z","signature_b64":"6HliFVuW4v77WCDpkn6AkW6gFXpQ0cZQfeHqbBO6+mLCO+ZmKM4lj1/lXKKG6JJbeRPD78UnlizbYhX+odseAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ec7cba2c905107506425a4196c010a1186abbeb765228fcaf549847ffb02e47b","last_reissued_at":"2026-05-18T00:04:38.363003Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:38.363003Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CNN Based Posture-Free Hand Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Richard Adiguna, Yustinus Eko Soelistio","submitted_at":"2018-09-27T10:00:31Z","abstract_excerpt":"Although many studies suggest high performance hand detection methods, those methods are likely to be overfitting. Fortunately, the Convolution Neural Network (CNN) based approach provides a better way that is less sensitive to translation and hand poses. However the CNN approach is complex and can increase computational time, which at the end reduce its effectiveness on a system where the speed is essential.In this study we propose a shallow CNN network which is fast, and insensitive to translation and hand poses. It is tested on two different domains of hand datasets, and performs in relativ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.10432","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":"1809.10432","created_at":"2026-05-18T00:04:38.363066+00:00"},{"alias_kind":"arxiv_version","alias_value":"1809.10432v1","created_at":"2026-05-18T00:04:38.363066+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.10432","created_at":"2026-05-18T00:04:38.363066+00:00"},{"alias_kind":"pith_short_12","alias_value":"5R6LULEQKEDV","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_16","alias_value":"5R6LULEQKEDVAZBF","created_at":"2026-05-18T12:32:08.215937+00:00"},{"alias_kind":"pith_short_8","alias_value":"5R6LULEQ","created_at":"2026-05-18T12:32:08.215937+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/5R6LULEQKEDVAZBFUQMWYAIKCG","json":"https://pith.science/pith/5R6LULEQKEDVAZBFUQMWYAIKCG.json","graph_json":"https://pith.science/api/pith-number/5R6LULEQKEDVAZBFUQMWYAIKCG/graph.json","events_json":"https://pith.science/api/pith-number/5R6LULEQKEDVAZBFUQMWYAIKCG/events.json","paper":"https://pith.science/paper/5R6LULEQ"},"agent_actions":{"view_html":"https://pith.science/pith/5R6LULEQKEDVAZBFUQMWYAIKCG","download_json":"https://pith.science/pith/5R6LULEQKEDVAZBFUQMWYAIKCG.json","view_paper":"https://pith.science/paper/5R6LULEQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1809.10432&json=true","fetch_graph":"https://pith.science/api/pith-number/5R6LULEQKEDVAZBFUQMWYAIKCG/graph.json","fetch_events":"https://pith.science/api/pith-number/5R6LULEQKEDVAZBFUQMWYAIKCG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5R6LULEQKEDVAZBFUQMWYAIKCG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5R6LULEQKEDVAZBFUQMWYAIKCG/action/storage_attestation","attest_author":"https://pith.science/pith/5R6LULEQKEDVAZBFUQMWYAIKCG/action/author_attestation","sign_citation":"https://pith.science/pith/5R6LULEQKEDVAZBFUQMWYAIKCG/action/citation_signature","submit_replication":"https://pith.science/pith/5R6LULEQKEDVAZBFUQMWYAIKCG/action/replication_record"}},"created_at":"2026-05-18T00:04:38.363066+00:00","updated_at":"2026-05-18T00:04:38.363066+00:00"}