{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:MCRKENTTEFGGFX54LOGDSJGKBU","short_pith_number":"pith:MCRKENTT","schema_version":"1.0","canonical_sha256":"60a2a23673214c62dfbc5b8c3924ca0d012c77aa6f8de16b87c20c1aef31926f","source":{"kind":"arxiv","id":"1505.01257","version":1},"attestation_state":"computed","paper":{"title":"A Deeper Look at Dataset Bias","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Barbara Caputo, Novi Patricia, Tatiana Tommasi, Tinne Tuytelaars","submitted_at":"2015-05-06T06:19:23Z","abstract_excerpt":"The presence of a bias in each image data collection has recently attracted a lot of attention in the computer vision community showing the limits in generalization of any learning method trained on a specific dataset. At the same time, with the rapid development of deep learning architectures, the activation values of Convolutional Neural Networks (CNN) are emerging as reliable and robust image descriptors. In this paper we propose to verify the potential of the DeCAF features when facing the dataset bias problem. We conduct a series of analyses looking at how existing datasets differ among e"},"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":"1505.01257","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-05-06T06:19:23Z","cross_cats_sorted":[],"title_canon_sha256":"d26ac31a74031b7b7410212f7019e55109abf9bfa2d8717928151cb546a56e25","abstract_canon_sha256":"d8d67011d9b516e3d6783936245eb0d08d3840d60dbd4415ace697a029a942f9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:16:50.004733Z","signature_b64":"CTPByhbm1ueDppHnHob8MiGpL7jdC+n0XYPxANHLgJ/b+jlvh7UGkcH7qPJ08TiuA9AnL+bzM7SVwijcwVI6BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"60a2a23673214c62dfbc5b8c3924ca0d012c77aa6f8de16b87c20c1aef31926f","last_reissued_at":"2026-05-18T02:16:50.004076Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:16:50.004076Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Deeper Look at Dataset Bias","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Barbara Caputo, Novi Patricia, Tatiana Tommasi, Tinne Tuytelaars","submitted_at":"2015-05-06T06:19:23Z","abstract_excerpt":"The presence of a bias in each image data collection has recently attracted a lot of attention in the computer vision community showing the limits in generalization of any learning method trained on a specific dataset. At the same time, with the rapid development of deep learning architectures, the activation values of Convolutional Neural Networks (CNN) are emerging as reliable and robust image descriptors. In this paper we propose to verify the potential of the DeCAF features when facing the dataset bias problem. We conduct a series of analyses looking at how existing datasets differ among e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1505.01257","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":"1505.01257","created_at":"2026-05-18T02:16:50.004162+00:00"},{"alias_kind":"arxiv_version","alias_value":"1505.01257v1","created_at":"2026-05-18T02:16:50.004162+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1505.01257","created_at":"2026-05-18T02:16:50.004162+00:00"},{"alias_kind":"pith_short_12","alias_value":"MCRKENTTEFGG","created_at":"2026-05-18T12:29:32.376354+00:00"},{"alias_kind":"pith_short_16","alias_value":"MCRKENTTEFGGFX54","created_at":"2026-05-18T12:29:32.376354+00:00"},{"alias_kind":"pith_short_8","alias_value":"MCRKENTT","created_at":"2026-05-18T12:29:32.376354+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/MCRKENTTEFGGFX54LOGDSJGKBU","json":"https://pith.science/pith/MCRKENTTEFGGFX54LOGDSJGKBU.json","graph_json":"https://pith.science/api/pith-number/MCRKENTTEFGGFX54LOGDSJGKBU/graph.json","events_json":"https://pith.science/api/pith-number/MCRKENTTEFGGFX54LOGDSJGKBU/events.json","paper":"https://pith.science/paper/MCRKENTT"},"agent_actions":{"view_html":"https://pith.science/pith/MCRKENTTEFGGFX54LOGDSJGKBU","download_json":"https://pith.science/pith/MCRKENTTEFGGFX54LOGDSJGKBU.json","view_paper":"https://pith.science/paper/MCRKENTT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1505.01257&json=true","fetch_graph":"https://pith.science/api/pith-number/MCRKENTTEFGGFX54LOGDSJGKBU/graph.json","fetch_events":"https://pith.science/api/pith-number/MCRKENTTEFGGFX54LOGDSJGKBU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MCRKENTTEFGGFX54LOGDSJGKBU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MCRKENTTEFGGFX54LOGDSJGKBU/action/storage_attestation","attest_author":"https://pith.science/pith/MCRKENTTEFGGFX54LOGDSJGKBU/action/author_attestation","sign_citation":"https://pith.science/pith/MCRKENTTEFGGFX54LOGDSJGKBU/action/citation_signature","submit_replication":"https://pith.science/pith/MCRKENTTEFGGFX54LOGDSJGKBU/action/replication_record"}},"created_at":"2026-05-18T02:16:50.004162+00:00","updated_at":"2026-05-18T02:16:50.004162+00:00"}