{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:W7WPQ5QLE6C3KEXCS5VMWFVW4P","short_pith_number":"pith:W7WPQ5QL","schema_version":"1.0","canonical_sha256":"b7ecf8760b2785b512e2976acb16b6e3df4c56cb816fa0c8772e78028cfcfaf7","source":{"kind":"arxiv","id":"2405.19351","version":1},"attestation_state":"computed","paper":{"title":"Resonate-and-Fire Spiking Neurons for Target Detection and Hand Gesture Recognition: A Hybrid Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"eess.SP","authors_text":"Ahmed Shaaban, Fabian Lurz, Maximilian Strobel, Robert Weigel, Wolfgang Furtner, Zeineb Chaabouni","submitted_at":"2024-05-22T14:40:02Z","abstract_excerpt":"Hand gesture recognition using radar often relies on computationally expensive fast Fourier transforms. This paper proposes an alternative approach that bypasses fast Fourier transforms using resonate-and-fire neurons. These neurons directly detect the hand in the time-domain signal, eliminating the need for fast Fourier transforms to retrieve range information. Following detection, a simple Goertzel algorithm is employed to extract five key features, eliminating the need for a second fast Fourier transform. These features are then fed into a recurrent neural network, achieving an accuracy of "},"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":"2405.19351","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2024-05-22T14:40:02Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"b07779d95e361443bcceee277218fd9fabf1022174401aa133d59df74bf13593","abstract_canon_sha256":"76b8793067288b7e38583a5da0586523985f3d4f0b743af13222d38939930869"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:25:35.170349Z","signature_b64":"cL1A/BTN0kXjBKMyPYY5RccTDr1ZuaDKzYb/6/p7fRBL3iwIgh86AzAocnxAA2arUohfZSzjNcMUkrB3jtAQDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7ecf8760b2785b512e2976acb16b6e3df4c56cb816fa0c8772e78028cfcfaf7","last_reissued_at":"2026-07-05T08:25:35.169931Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:25:35.169931Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Resonate-and-Fire Spiking Neurons for Target Detection and Hand Gesture Recognition: A Hybrid Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"eess.SP","authors_text":"Ahmed Shaaban, Fabian Lurz, Maximilian Strobel, Robert Weigel, Wolfgang Furtner, Zeineb Chaabouni","submitted_at":"2024-05-22T14:40:02Z","abstract_excerpt":"Hand gesture recognition using radar often relies on computationally expensive fast Fourier transforms. This paper proposes an alternative approach that bypasses fast Fourier transforms using resonate-and-fire neurons. These neurons directly detect the hand in the time-domain signal, eliminating the need for fast Fourier transforms to retrieve range information. Following detection, a simple Goertzel algorithm is employed to extract five key features, eliminating the need for a second fast Fourier transform. These features are then fed into a recurrent neural network, achieving an accuracy of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.19351","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2405.19351/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2405.19351","created_at":"2026-07-05T08:25:35.169985+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.19351v1","created_at":"2026-07-05T08:25:35.169985+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.19351","created_at":"2026-07-05T08:25:35.169985+00:00"},{"alias_kind":"pith_short_12","alias_value":"W7WPQ5QLE6C3","created_at":"2026-07-05T08:25:35.169985+00:00"},{"alias_kind":"pith_short_16","alias_value":"W7WPQ5QLE6C3KEXC","created_at":"2026-07-05T08:25:35.169985+00:00"},{"alias_kind":"pith_short_8","alias_value":"W7WPQ5QL","created_at":"2026-07-05T08:25:35.169985+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.13516","citing_title":"Adaptive-Frequency Resonate-and-Fire Neurons for Spectral Estimation of Streaming Radar Signals","ref_index":17,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/W7WPQ5QLE6C3KEXCS5VMWFVW4P","json":"https://pith.science/pith/W7WPQ5QLE6C3KEXCS5VMWFVW4P.json","graph_json":"https://pith.science/api/pith-number/W7WPQ5QLE6C3KEXCS5VMWFVW4P/graph.json","events_json":"https://pith.science/api/pith-number/W7WPQ5QLE6C3KEXCS5VMWFVW4P/events.json","paper":"https://pith.science/paper/W7WPQ5QL"},"agent_actions":{"view_html":"https://pith.science/pith/W7WPQ5QLE6C3KEXCS5VMWFVW4P","download_json":"https://pith.science/pith/W7WPQ5QLE6C3KEXCS5VMWFVW4P.json","view_paper":"https://pith.science/paper/W7WPQ5QL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.19351&json=true","fetch_graph":"https://pith.science/api/pith-number/W7WPQ5QLE6C3KEXCS5VMWFVW4P/graph.json","fetch_events":"https://pith.science/api/pith-number/W7WPQ5QLE6C3KEXCS5VMWFVW4P/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W7WPQ5QLE6C3KEXCS5VMWFVW4P/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W7WPQ5QLE6C3KEXCS5VMWFVW4P/action/storage_attestation","attest_author":"https://pith.science/pith/W7WPQ5QLE6C3KEXCS5VMWFVW4P/action/author_attestation","sign_citation":"https://pith.science/pith/W7WPQ5QLE6C3KEXCS5VMWFVW4P/action/citation_signature","submit_replication":"https://pith.science/pith/W7WPQ5QLE6C3KEXCS5VMWFVW4P/action/replication_record"}},"created_at":"2026-07-05T08:25:35.169985+00:00","updated_at":"2026-07-05T08:25:35.169985+00:00"}