{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:SBXVL5J4VRZSV7DUODDGLCONXP","short_pith_number":"pith:SBXVL5J4","schema_version":"1.0","canonical_sha256":"906f55f53cac732afc7470c66589cdbbc7e1c816571525fa5ecf9f7e5d7d7610","source":{"kind":"arxiv","id":"1507.08286","version":1},"attestation_state":"computed","paper":{"title":"Deep Learning for Single-View Instance Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE","cs.RO"],"primary_cat":"cs.CV","authors_text":"David Held, Sebastian Thrun, Silvio Savarese","submitted_at":"2015-07-29T20:11:12Z","abstract_excerpt":"Deep learning methods have typically been trained on large datasets in which many training examples are available. However, many real-world product datasets have only a small number of images available for each product. We explore the use of deep learning methods for recognizing object instances when we have only a single training example per class. We show that feedforward neural networks outperform state-of-the-art methods for recognizing objects from novel viewpoints even when trained from just a single image per object. To further improve our performance on this task, we propose to take ad"},"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":"1507.08286","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-07-29T20:11:12Z","cross_cats_sorted":["cs.LG","cs.NE","cs.RO"],"title_canon_sha256":"9aa92d5b732182b531c52d282a5838f22eea8926417e5a711b7e1f020272e2ee","abstract_canon_sha256":"012b9ee8aab139527aec7ac55136915f1281ed9a158f020624ff61cad9c75e81"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:36:07.818169Z","signature_b64":"L7jWFiln4MT7Bbgcer/gBtB+C78XEs8kv5zL5xnB+j7EzsF2Ugif67jJazJFdx84DhkaUxB8uj9sEUzt/C2PDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"906f55f53cac732afc7470c66589cdbbc7e1c816571525fa5ecf9f7e5d7d7610","last_reissued_at":"2026-05-18T01:36:07.817705Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:36:07.817705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Deep Learning for Single-View Instance Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE","cs.RO"],"primary_cat":"cs.CV","authors_text":"David Held, Sebastian Thrun, Silvio Savarese","submitted_at":"2015-07-29T20:11:12Z","abstract_excerpt":"Deep learning methods have typically been trained on large datasets in which many training examples are available. However, many real-world product datasets have only a small number of images available for each product. We explore the use of deep learning methods for recognizing object instances when we have only a single training example per class. We show that feedforward neural networks outperform state-of-the-art methods for recognizing objects from novel viewpoints even when trained from just a single image per object. To further improve our performance on this task, we propose to take ad"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1507.08286","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":"1507.08286","created_at":"2026-05-18T01:36:07.817765+00:00"},{"alias_kind":"arxiv_version","alias_value":"1507.08286v1","created_at":"2026-05-18T01:36:07.817765+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1507.08286","created_at":"2026-05-18T01:36:07.817765+00:00"},{"alias_kind":"pith_short_12","alias_value":"SBXVL5J4VRZS","created_at":"2026-05-18T12:29:39.896362+00:00"},{"alias_kind":"pith_short_16","alias_value":"SBXVL5J4VRZSV7DU","created_at":"2026-05-18T12:29:39.896362+00:00"},{"alias_kind":"pith_short_8","alias_value":"SBXVL5J4","created_at":"2026-05-18T12:29:39.896362+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/SBXVL5J4VRZSV7DUODDGLCONXP","json":"https://pith.science/pith/SBXVL5J4VRZSV7DUODDGLCONXP.json","graph_json":"https://pith.science/api/pith-number/SBXVL5J4VRZSV7DUODDGLCONXP/graph.json","events_json":"https://pith.science/api/pith-number/SBXVL5J4VRZSV7DUODDGLCONXP/events.json","paper":"https://pith.science/paper/SBXVL5J4"},"agent_actions":{"view_html":"https://pith.science/pith/SBXVL5J4VRZSV7DUODDGLCONXP","download_json":"https://pith.science/pith/SBXVL5J4VRZSV7DUODDGLCONXP.json","view_paper":"https://pith.science/paper/SBXVL5J4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1507.08286&json=true","fetch_graph":"https://pith.science/api/pith-number/SBXVL5J4VRZSV7DUODDGLCONXP/graph.json","fetch_events":"https://pith.science/api/pith-number/SBXVL5J4VRZSV7DUODDGLCONXP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SBXVL5J4VRZSV7DUODDGLCONXP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SBXVL5J4VRZSV7DUODDGLCONXP/action/storage_attestation","attest_author":"https://pith.science/pith/SBXVL5J4VRZSV7DUODDGLCONXP/action/author_attestation","sign_citation":"https://pith.science/pith/SBXVL5J4VRZSV7DUODDGLCONXP/action/citation_signature","submit_replication":"https://pith.science/pith/SBXVL5J4VRZSV7DUODDGLCONXP/action/replication_record"}},"created_at":"2026-05-18T01:36:07.817765+00:00","updated_at":"2026-05-18T01:36:07.817765+00:00"}