{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:JRAQFXO7GRZPSP7V4DXPHUSKPI","short_pith_number":"pith:JRAQFXO7","schema_version":"1.0","canonical_sha256":"4c4102dddf3472f93ff5e0eef3d24a7a17235c513bf9f0c227c50747f32c68af","source":{"kind":"arxiv","id":"1811.08352","version":1},"attestation_state":"computed","paper":{"title":"Near Real-Time Object Recognition for Pepper based on Deep Neural Networks Running on a Backpack","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Cristopher G\\'omez, Esteban Norambuena, Esteban Reyes, Javier Ruiz-del-Solar","submitted_at":"2018-11-20T16:32:54Z","abstract_excerpt":"The main goal of the paper is to provide Pepper with a near real-time object recognition system based on deep neural networks. The proposed system is based on YOLO (You Only Look Once), a deep neural network that is able to detect and recognize objects robustly and at a high speed. In addition, considering that YOLO cannot be run in the Pepper's internal computer in near real-time, we propose to use a Backpack for Pepper, which holds a Jetson TK1 card and a battery. By using this card, Pepper is able to robustly detect and recognize objects in images of 320x320 pixels at about 5 frames per sec"},"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":"1811.08352","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2018-11-20T16:32:54Z","cross_cats_sorted":[],"title_canon_sha256":"a4014a50973dd3cc97ddf284351f58a3fbcc2709c887af815e95fd9f44169aac","abstract_canon_sha256":"5f7ddbe55847dbd60ed070445c360a27a79b5d4facdf9baefe4cf7db10ce082f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:14.284890Z","signature_b64":"5GalOLPNhFf8RxrQC5hHKbpFHSyJmsvs6TqcWhjxWHNL4cg1kjkU3/UHwyo70x+++K5rYv20XjRm8tam7zUpAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4c4102dddf3472f93ff5e0eef3d24a7a17235c513bf9f0c227c50747f32c68af","last_reissued_at":"2026-05-18T00:00:14.284390Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:14.284390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Near Real-Time Object Recognition for Pepper based on Deep Neural Networks Running on a Backpack","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Cristopher G\\'omez, Esteban Norambuena, Esteban Reyes, Javier Ruiz-del-Solar","submitted_at":"2018-11-20T16:32:54Z","abstract_excerpt":"The main goal of the paper is to provide Pepper with a near real-time object recognition system based on deep neural networks. The proposed system is based on YOLO (You Only Look Once), a deep neural network that is able to detect and recognize objects robustly and at a high speed. In addition, considering that YOLO cannot be run in the Pepper's internal computer in near real-time, we propose to use a Backpack for Pepper, which holds a Jetson TK1 card and a battery. By using this card, Pepper is able to robustly detect and recognize objects in images of 320x320 pixels at about 5 frames per sec"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.08352","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":"1811.08352","created_at":"2026-05-18T00:00:14.284487+00:00"},{"alias_kind":"arxiv_version","alias_value":"1811.08352v1","created_at":"2026-05-18T00:00:14.284487+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.08352","created_at":"2026-05-18T00:00:14.284487+00:00"},{"alias_kind":"pith_short_12","alias_value":"JRAQFXO7GRZP","created_at":"2026-05-18T12:32:31.084164+00:00"},{"alias_kind":"pith_short_16","alias_value":"JRAQFXO7GRZPSP7V","created_at":"2026-05-18T12:32:31.084164+00:00"},{"alias_kind":"pith_short_8","alias_value":"JRAQFXO7","created_at":"2026-05-18T12:32:31.084164+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/JRAQFXO7GRZPSP7V4DXPHUSKPI","json":"https://pith.science/pith/JRAQFXO7GRZPSP7V4DXPHUSKPI.json","graph_json":"https://pith.science/api/pith-number/JRAQFXO7GRZPSP7V4DXPHUSKPI/graph.json","events_json":"https://pith.science/api/pith-number/JRAQFXO7GRZPSP7V4DXPHUSKPI/events.json","paper":"https://pith.science/paper/JRAQFXO7"},"agent_actions":{"view_html":"https://pith.science/pith/JRAQFXO7GRZPSP7V4DXPHUSKPI","download_json":"https://pith.science/pith/JRAQFXO7GRZPSP7V4DXPHUSKPI.json","view_paper":"https://pith.science/paper/JRAQFXO7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1811.08352&json=true","fetch_graph":"https://pith.science/api/pith-number/JRAQFXO7GRZPSP7V4DXPHUSKPI/graph.json","fetch_events":"https://pith.science/api/pith-number/JRAQFXO7GRZPSP7V4DXPHUSKPI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JRAQFXO7GRZPSP7V4DXPHUSKPI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JRAQFXO7GRZPSP7V4DXPHUSKPI/action/storage_attestation","attest_author":"https://pith.science/pith/JRAQFXO7GRZPSP7V4DXPHUSKPI/action/author_attestation","sign_citation":"https://pith.science/pith/JRAQFXO7GRZPSP7V4DXPHUSKPI/action/citation_signature","submit_replication":"https://pith.science/pith/JRAQFXO7GRZPSP7V4DXPHUSKPI/action/replication_record"}},"created_at":"2026-05-18T00:00:14.284487+00:00","updated_at":"2026-05-18T00:00:14.284487+00:00"}