{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:H6WZQQW6WPTWVAN66OJXFD6FZK","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":"3d5b079d83cdbdff5e1dbe2781a49a4e1082c9d33fdd593878c444339272c777","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2021-06-04T13:07:20Z","title_canon_sha256":"125e8924f67ae9dcab89c434c13ea2723d0a1aa24b1dcf187b973a7fc0522300"},"schema_version":"1.0","source":{"id":"2106.02463","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.02463","created_at":"2026-07-05T02:48:23Z"},{"alias_kind":"arxiv_version","alias_value":"2106.02463v2","created_at":"2026-07-05T02:48:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.02463","created_at":"2026-07-05T02:48:23Z"},{"alias_kind":"pith_short_12","alias_value":"H6WZQQW6WPTW","created_at":"2026-07-05T02:48:23Z"},{"alias_kind":"pith_short_16","alias_value":"H6WZQQW6WPTWVAN6","created_at":"2026-07-05T02:48:23Z"},{"alias_kind":"pith_short_8","alias_value":"H6WZQQW6","created_at":"2026-07-05T02:48:23Z"}],"graph_snapshots":[{"event_id":"sha256:4ab2270dcff7dbd2b0ed20c81118772d63ff82919b972ff2fd024cdff7ead702","target":"graph","created_at":"2026-07-05T02:48:23Z","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/2106.02463/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In EMG based pattern recognition (EMG-PR), deep learning-based techniques have become more prominent for their self-regulating capability to extract discriminant features from large data-sets. Moreover, the performance of traditional machine learning-based methods show limitation to categorize over a certain number of classes and degrades over a period of time. In this paper, an accurate, robust, and fast convolutional neural network-based framework for EMG pattern identification is presented. To assess the performance of the proposed system, five publicly available and benchmark data-sets of ","authors_text":"Amit M. Joshi, Deepak Joshi, Sidharth Pancholi","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2021-06-04T13:07:20Z","title":"A Robust and Accurate Deep Learning based Pattern Recognition Framework for Upper Limb Prosthesis using sEMG"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.02463","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":"sha256:62ddfe33cdb455ae9023d90bf0d31cd23de8e0a11c844f4ba8d01cfa9562f338","target":"record","created_at":"2026-07-05T02:48:23Z","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":"3d5b079d83cdbdff5e1dbe2781a49a4e1082c9d33fdd593878c444339272c777","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2021-06-04T13:07:20Z","title_canon_sha256":"125e8924f67ae9dcab89c434c13ea2723d0a1aa24b1dcf187b973a7fc0522300"},"schema_version":"1.0","source":{"id":"2106.02463","kind":"arxiv","version":2}},"canonical_sha256":"3fad9842deb3e76a81bef393728fc5caac3acf6d0126d7bc45b2ee890d9f59be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3fad9842deb3e76a81bef393728fc5caac3acf6d0126d7bc45b2ee890d9f59be","first_computed_at":"2026-07-05T02:48:23.674573Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:48:23.674573Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3lWCd8BU4JKb72JYIDrF68lFsNgr5zBXNaosgDGv7ErBxK3cvbnXyDIFn5E6eqDrefSJIJWgfhPqUVHQnF7UDw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:48:23.674980Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.02463","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:62ddfe33cdb455ae9023d90bf0d31cd23de8e0a11c844f4ba8d01cfa9562f338","sha256:4ab2270dcff7dbd2b0ed20c81118772d63ff82919b972ff2fd024cdff7ead702"],"state_sha256":"0539dca3cf17d4d871e19c14f7f0b15a37d25770b4b8353e331ad976f8d10b8b"}