{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:YD4H4VZCC7UVTI7O66RT2DYHO3","short_pith_number":"pith:YD4H4VZC","canonical_record":{"source":{"id":"1503.04065","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-03-13T13:49:26Z","cross_cats_sorted":[],"title_canon_sha256":"aa12f67227abf77a698e3dbee107216b7f1434435be0c1100635d47e5ce2c9bf","abstract_canon_sha256":"ebfa4784e5ab7c3899f97d68768e0b782929cdec51b0d129e813e28b6b8204aa"},"schema_version":"1.0"},"canonical_sha256":"c0f87e572217e959a3eef7a33d0f0776f02e6e1ec398791fd66400429322b244","source":{"kind":"arxiv","id":"1503.04065","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.04065","created_at":"2026-05-18T02:23:57Z"},{"alias_kind":"arxiv_version","alias_value":"1503.04065v1","created_at":"2026-05-18T02:23:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.04065","created_at":"2026-05-18T02:23:57Z"},{"alias_kind":"pith_short_12","alias_value":"YD4H4VZCC7UV","created_at":"2026-05-18T12:29:50Z"},{"alias_kind":"pith_short_16","alias_value":"YD4H4VZCC7UVTI7O","created_at":"2026-05-18T12:29:50Z"},{"alias_kind":"pith_short_8","alias_value":"YD4H4VZC","created_at":"2026-05-18T12:29:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:YD4H4VZCC7UVTI7O66RT2DYHO3","target":"record","payload":{"canonical_record":{"source":{"id":"1503.04065","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-03-13T13:49:26Z","cross_cats_sorted":[],"title_canon_sha256":"aa12f67227abf77a698e3dbee107216b7f1434435be0c1100635d47e5ce2c9bf","abstract_canon_sha256":"ebfa4784e5ab7c3899f97d68768e0b782929cdec51b0d129e813e28b6b8204aa"},"schema_version":"1.0"},"canonical_sha256":"c0f87e572217e959a3eef7a33d0f0776f02e6e1ec398791fd66400429322b244","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:23:57.194071Z","signature_b64":"9P/cHmOf74m1jFUrnk0HHmBpMJaZGFrPNhrluimNDwIURCm2sy+r/DUR4owzJ2BN/JsPyNTcz4sXmIPpmHo/Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c0f87e572217e959a3eef7a33d0f0776f02e6e1ec398791fd66400429322b244","last_reissued_at":"2026-05-18T02:23:57.193368Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:23:57.193368Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1503.04065","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:23:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aLrCxhAjnxuxTn6PydMNy+XvqkLlnzuqXAK6ZPCp+O6tpXLR4r7Vk0JUO6WnrdOz3Bz3rSwX7RT/03jIXgTyCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T03:19:38.766961Z"},"content_sha256":"f4ffae0dc3dce531b98b58000ca788b3b1008fb5b1850be1add34a1f9c771fa5","schema_version":"1.0","event_id":"sha256:f4ffae0dc3dce531b98b58000ca788b3b1008fb5b1850be1add34a1f9c771fa5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:YD4H4VZCC7UVTI7O66RT2DYHO3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hybrid multi-layer Deep CNN/Aggregator feature for image classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Frederic Jurie, Joaquin Zepeda, Louis Chevallier, Patrick Perez, Praveen Kulkarni","submitted_at":"2015-03-13T13:49:26Z","abstract_excerpt":"Deep Convolutional Neural Networks (DCNN) have established a remarkable performance benchmark in the field of image classification, displacing classical approaches based on hand-tailored aggregations of local descriptors. Yet DCNNs impose high computational burdens both at training and at testing time, and training them requires collecting and annotating large amounts of training data. Supervised adaptation methods have been proposed in the literature that partially re-learn a transferred DCNN structure from a new target dataset. Yet these require expensive bounding-box annotations and are sti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.04065","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:23:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RsyLUTrr4N13P/mt4DL4iHkGuxyTbCsU/h4w0s4J6UXXJR6K6oIlpCLkm2c6oP984gUeU1Kj/HTiM3iWzBkkCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T03:19:38.767617Z"},"content_sha256":"45002da54aaf959585d82363bcdbb8dcd751491ca8d27f0bc7e0603db58a13c0","schema_version":"1.0","event_id":"sha256:45002da54aaf959585d82363bcdbb8dcd751491ca8d27f0bc7e0603db58a13c0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YD4H4VZCC7UVTI7O66RT2DYHO3/bundle.json","state_url":"https://pith.science/pith/YD4H4VZCC7UVTI7O66RT2DYHO3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YD4H4VZCC7UVTI7O66RT2DYHO3/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-27T03:19:38Z","links":{"resolver":"https://pith.science/pith/YD4H4VZCC7UVTI7O66RT2DYHO3","bundle":"https://pith.science/pith/YD4H4VZCC7UVTI7O66RT2DYHO3/bundle.json","state":"https://pith.science/pith/YD4H4VZCC7UVTI7O66RT2DYHO3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YD4H4VZCC7UVTI7O66RT2DYHO3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:YD4H4VZCC7UVTI7O66RT2DYHO3","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"ebfa4784e5ab7c3899f97d68768e0b782929cdec51b0d129e813e28b6b8204aa","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-03-13T13:49:26Z","title_canon_sha256":"aa12f67227abf77a698e3dbee107216b7f1434435be0c1100635d47e5ce2c9bf"},"schema_version":"1.0","source":{"id":"1503.04065","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1503.04065","created_at":"2026-05-18T02:23:57Z"},{"alias_kind":"arxiv_version","alias_value":"1503.04065v1","created_at":"2026-05-18T02:23:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1503.04065","created_at":"2026-05-18T02:23:57Z"},{"alias_kind":"pith_short_12","alias_value":"YD4H4VZCC7UV","created_at":"2026-05-18T12:29:50Z"},{"alias_kind":"pith_short_16","alias_value":"YD4H4VZCC7UVTI7O","created_at":"2026-05-18T12:29:50Z"},{"alias_kind":"pith_short_8","alias_value":"YD4H4VZC","created_at":"2026-05-18T12:29:50Z"}],"graph_snapshots":[{"event_id":"sha256:45002da54aaf959585d82363bcdbb8dcd751491ca8d27f0bc7e0603db58a13c0","target":"graph","created_at":"2026-05-18T02:23:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Deep Convolutional Neural Networks (DCNN) have established a remarkable performance benchmark in the field of image classification, displacing classical approaches based on hand-tailored aggregations of local descriptors. Yet DCNNs impose high computational burdens both at training and at testing time, and training them requires collecting and annotating large amounts of training data. Supervised adaptation methods have been proposed in the literature that partially re-learn a transferred DCNN structure from a new target dataset. Yet these require expensive bounding-box annotations and are sti","authors_text":"Frederic Jurie, Joaquin Zepeda, Louis Chevallier, Patrick Perez, Praveen Kulkarni","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-03-13T13:49:26Z","title":"Hybrid multi-layer Deep CNN/Aggregator feature for image classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1503.04065","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:f4ffae0dc3dce531b98b58000ca788b3b1008fb5b1850be1add34a1f9c771fa5","target":"record","created_at":"2026-05-18T02:23:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"ebfa4784e5ab7c3899f97d68768e0b782929cdec51b0d129e813e28b6b8204aa","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2015-03-13T13:49:26Z","title_canon_sha256":"aa12f67227abf77a698e3dbee107216b7f1434435be0c1100635d47e5ce2c9bf"},"schema_version":"1.0","source":{"id":"1503.04065","kind":"arxiv","version":1}},"canonical_sha256":"c0f87e572217e959a3eef7a33d0f0776f02e6e1ec398791fd66400429322b244","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c0f87e572217e959a3eef7a33d0f0776f02e6e1ec398791fd66400429322b244","first_computed_at":"2026-05-18T02:23:57.193368Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:23:57.193368Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9P/cHmOf74m1jFUrnk0HHmBpMJaZGFrPNhrluimNDwIURCm2sy+r/DUR4owzJ2BN/JsPyNTcz4sXmIPpmHo/Cg==","signature_status":"signed_v1","signed_at":"2026-05-18T02:23:57.194071Z","signed_message":"canonical_sha256_bytes"},"source_id":"1503.04065","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f4ffae0dc3dce531b98b58000ca788b3b1008fb5b1850be1add34a1f9c771fa5","sha256:45002da54aaf959585d82363bcdbb8dcd751491ca8d27f0bc7e0603db58a13c0"],"state_sha256":"ba94cc20d9d701ded21e5cdc2699945dd901ae27c37bcf228e1242ea4f1ffdc5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"op8qij5ho7vpzvhAmEmOMRL5votVJfvsZhr7u5I+jBkeDQCXsVyu9BfVqEldHxmiBparSIUzW/DD1eoFbwthCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T03:19:38.770593Z","bundle_sha256":"1d17073a11c21a5a9479fe6e5194f741f3e57f7c429469ef633170f352b3e714"}}