{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:HSAPMABXWMUXSAJHGOLSQWNFVX","short_pith_number":"pith:HSAPMABX","schema_version":"1.0","canonical_sha256":"3c80f60037b32979012733972859a5adfaab8f565b1e9201501124f7b3eb72fe","source":{"kind":"arxiv","id":"2002.09821","version":1},"attestation_state":"computed","paper":{"title":"A Multi-view CNN-based Acoustic Classification System for Automatic Animal Species Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SD"],"primary_cat":"eess.AS","authors_text":"Bo Wei, Lina Yao, Wanli Xue, Weitao Xu, Xiang Zhang","submitted_at":"2020-02-23T03:51:08Z","abstract_excerpt":"Automatic identification of animal species by their vocalization is an important and challenging task. Although many kinds of audio monitoring system have been proposed in the literature, they suffer from several disadvantages such as non-trivial feature selection, accuracy degradation because of environmental noise or intensive local computation. In this paper, we propose a deep learning based acoustic classification framework for Wireless Acoustic Sensor Network (WASN). The proposed framework is based on cloud architecture which relaxes the computational burden on the wireless sensor node. T"},"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":"2002.09821","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.AS","submitted_at":"2020-02-23T03:51:08Z","cross_cats_sorted":["cs.LG","cs.SD"],"title_canon_sha256":"721a9426b3437573850b19f3fab1aa197437e5dc9a46cd8ed09964ce374e0b46","abstract_canon_sha256":"cabe2ddda10e285d97f0e7c1db53f777c8c477251c65552d472ce292a1187182"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:43:11.952307Z","signature_b64":"5d3Yw8rJQ0w6pa99xv65FTh9dR6KprLBpH/2XUVySgftt1bLUnCb+BdZrzV7ujx4xypiCcynO3VjYoi3Z2c8AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3c80f60037b32979012733972859a5adfaab8f565b1e9201501124f7b3eb72fe","last_reissued_at":"2026-07-05T00:43:11.951910Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:43:11.951910Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Multi-view CNN-based Acoustic Classification System for Automatic Animal Species Identification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.SD"],"primary_cat":"eess.AS","authors_text":"Bo Wei, Lina Yao, Wanli Xue, Weitao Xu, Xiang Zhang","submitted_at":"2020-02-23T03:51:08Z","abstract_excerpt":"Automatic identification of animal species by their vocalization is an important and challenging task. Although many kinds of audio monitoring system have been proposed in the literature, they suffer from several disadvantages such as non-trivial feature selection, accuracy degradation because of environmental noise or intensive local computation. In this paper, we propose a deep learning based acoustic classification framework for Wireless Acoustic Sensor Network (WASN). The proposed framework is based on cloud architecture which relaxes the computational burden on the wireless sensor node. T"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.09821","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/2002.09821/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":"2002.09821","created_at":"2026-07-05T00:43:11.951968+00:00"},{"alias_kind":"arxiv_version","alias_value":"2002.09821v1","created_at":"2026-07-05T00:43:11.951968+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.09821","created_at":"2026-07-05T00:43:11.951968+00:00"},{"alias_kind":"pith_short_12","alias_value":"HSAPMABXWMUX","created_at":"2026-07-05T00:43:11.951968+00:00"},{"alias_kind":"pith_short_16","alias_value":"HSAPMABXWMUXSAJH","created_at":"2026-07-05T00:43:11.951968+00:00"},{"alias_kind":"pith_short_8","alias_value":"HSAPMABX","created_at":"2026-07-05T00:43:11.951968+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/HSAPMABXWMUXSAJHGOLSQWNFVX","json":"https://pith.science/pith/HSAPMABXWMUXSAJHGOLSQWNFVX.json","graph_json":"https://pith.science/api/pith-number/HSAPMABXWMUXSAJHGOLSQWNFVX/graph.json","events_json":"https://pith.science/api/pith-number/HSAPMABXWMUXSAJHGOLSQWNFVX/events.json","paper":"https://pith.science/paper/HSAPMABX"},"agent_actions":{"view_html":"https://pith.science/pith/HSAPMABXWMUXSAJHGOLSQWNFVX","download_json":"https://pith.science/pith/HSAPMABXWMUXSAJHGOLSQWNFVX.json","view_paper":"https://pith.science/paper/HSAPMABX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2002.09821&json=true","fetch_graph":"https://pith.science/api/pith-number/HSAPMABXWMUXSAJHGOLSQWNFVX/graph.json","fetch_events":"https://pith.science/api/pith-number/HSAPMABXWMUXSAJHGOLSQWNFVX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HSAPMABXWMUXSAJHGOLSQWNFVX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HSAPMABXWMUXSAJHGOLSQWNFVX/action/storage_attestation","attest_author":"https://pith.science/pith/HSAPMABXWMUXSAJHGOLSQWNFVX/action/author_attestation","sign_citation":"https://pith.science/pith/HSAPMABXWMUXSAJHGOLSQWNFVX/action/citation_signature","submit_replication":"https://pith.science/pith/HSAPMABXWMUXSAJHGOLSQWNFVX/action/replication_record"}},"created_at":"2026-07-05T00:43:11.951968+00:00","updated_at":"2026-07-05T00:43:11.951968+00:00"}