{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:LMD2EYDPEDPFKIMOZVP4NFTSCI","short_pith_number":"pith:LMD2EYDP","schema_version":"1.0","canonical_sha256":"5b07a2606f20de55218ecd5fc69672123053ad209ddb3a13c3cd7e0481890888","source":{"kind":"arxiv","id":"1501.05495","version":1},"attestation_state":"computed","paper":{"title":"A GA Based approach for selection of local features for recognition of handwritten Bangla numerals","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Mahantapas Kundu, Mita Nasipuri, Nibaran Das, Punam Kumar Saha, Ram Sarkar, Subhadip Basu","submitted_at":"2015-01-22T13:46:06Z","abstract_excerpt":"Soft computing approaches are mainly designed to address the real world ill-defined, imprecisely formulated problems, combining different kind of novel models of computation, such as neural networks, genetic algorithms (GAs. Handwritten digit recognition is a typical example of one such problem. In the current work we have developed a two-pass approach where the first pass classifier performs a coarse classification, based on some global features of the input pattern by restricting the possibility of classification decisions within a group of classes, smaller than the number of classes conside"},"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":"1501.05495","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-01-22T13:46:06Z","cross_cats_sorted":[],"title_canon_sha256":"d5c8473128ee07f5540609358c8f584f66013169fd3e628fa1c79f1f97c353ca","abstract_canon_sha256":"45ac1a089dfa191f8bd1e53c68e953a4025af7786960428b512f1e73da4e0263"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:28:54.544707Z","signature_b64":"8SKqh3L1B2FdBFPDJ5u7uPrRCh5ZHXnPnLo2FpMWuTHYIi62yiQh7sZyYAgIn0KtgTItEZmzME8QhQJCiZ7iDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5b07a2606f20de55218ecd5fc69672123053ad209ddb3a13c3cd7e0481890888","last_reissued_at":"2026-05-18T02:28:54.544335Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:28:54.544335Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A GA Based approach for selection of local features for recognition of handwritten Bangla numerals","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Mahantapas Kundu, Mita Nasipuri, Nibaran Das, Punam Kumar Saha, Ram Sarkar, Subhadip Basu","submitted_at":"2015-01-22T13:46:06Z","abstract_excerpt":"Soft computing approaches are mainly designed to address the real world ill-defined, imprecisely formulated problems, combining different kind of novel models of computation, such as neural networks, genetic algorithms (GAs. Handwritten digit recognition is a typical example of one such problem. In the current work we have developed a two-pass approach where the first pass classifier performs a coarse classification, based on some global features of the input pattern by restricting the possibility of classification decisions within a group of classes, smaller than the number of classes conside"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1501.05495","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":"1501.05495","created_at":"2026-05-18T02:28:54.544399+00:00"},{"alias_kind":"arxiv_version","alias_value":"1501.05495v1","created_at":"2026-05-18T02:28:54.544399+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1501.05495","created_at":"2026-05-18T02:28:54.544399+00:00"},{"alias_kind":"pith_short_12","alias_value":"LMD2EYDPEDPF","created_at":"2026-05-18T12:29:29.992203+00:00"},{"alias_kind":"pith_short_16","alias_value":"LMD2EYDPEDPFKIMO","created_at":"2026-05-18T12:29:29.992203+00:00"},{"alias_kind":"pith_short_8","alias_value":"LMD2EYDP","created_at":"2026-05-18T12:29:29.992203+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/LMD2EYDPEDPFKIMOZVP4NFTSCI","json":"https://pith.science/pith/LMD2EYDPEDPFKIMOZVP4NFTSCI.json","graph_json":"https://pith.science/api/pith-number/LMD2EYDPEDPFKIMOZVP4NFTSCI/graph.json","events_json":"https://pith.science/api/pith-number/LMD2EYDPEDPFKIMOZVP4NFTSCI/events.json","paper":"https://pith.science/paper/LMD2EYDP"},"agent_actions":{"view_html":"https://pith.science/pith/LMD2EYDPEDPFKIMOZVP4NFTSCI","download_json":"https://pith.science/pith/LMD2EYDPEDPFKIMOZVP4NFTSCI.json","view_paper":"https://pith.science/paper/LMD2EYDP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1501.05495&json=true","fetch_graph":"https://pith.science/api/pith-number/LMD2EYDPEDPFKIMOZVP4NFTSCI/graph.json","fetch_events":"https://pith.science/api/pith-number/LMD2EYDPEDPFKIMOZVP4NFTSCI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LMD2EYDPEDPFKIMOZVP4NFTSCI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LMD2EYDPEDPFKIMOZVP4NFTSCI/action/storage_attestation","attest_author":"https://pith.science/pith/LMD2EYDPEDPFKIMOZVP4NFTSCI/action/author_attestation","sign_citation":"https://pith.science/pith/LMD2EYDPEDPFKIMOZVP4NFTSCI/action/citation_signature","submit_replication":"https://pith.science/pith/LMD2EYDPEDPFKIMOZVP4NFTSCI/action/replication_record"}},"created_at":"2026-05-18T02:28:54.544399+00:00","updated_at":"2026-05-18T02:28:54.544399+00:00"}