{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:3ITZTKOBUXGQ6SPI7H5UHVBWJT","short_pith_number":"pith:3ITZTKOB","canonical_record":{"source":{"id":"1410.3752","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-14T16:13:45Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"839cf1f7e4954e812e195dd33e9475436ba4ffffff85da3114976c8feb79b3be","abstract_canon_sha256":"a6d9c9f276c2c30f0675e7c394359e7ae8da8b2a6854e5b65f76fd16b60fd508"},"schema_version":"1.0"},"canonical_sha256":"da2799a9c1a5cd0f49e8f9fb43d4364cf8fec28df73a5e8aba560ec7bb4404be","source":{"kind":"arxiv","id":"1410.3752","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1410.3752","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"arxiv_version","alias_value":"1410.3752v1","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.3752","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"pith_short_12","alias_value":"3ITZTKOBUXGQ","created_at":"2026-05-18T12:28:11Z"},{"alias_kind":"pith_short_16","alias_value":"3ITZTKOBUXGQ6SPI","created_at":"2026-05-18T12:28:11Z"},{"alias_kind":"pith_short_8","alias_value":"3ITZTKOB","created_at":"2026-05-18T12:28:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:3ITZTKOBUXGQ6SPI7H5UHVBWJT","target":"record","payload":{"canonical_record":{"source":{"id":"1410.3752","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-14T16:13:45Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"839cf1f7e4954e812e195dd33e9475436ba4ffffff85da3114976c8feb79b3be","abstract_canon_sha256":"a6d9c9f276c2c30f0675e7c394359e7ae8da8b2a6854e5b65f76fd16b60fd508"},"schema_version":"1.0"},"canonical_sha256":"da2799a9c1a5cd0f49e8f9fb43d4364cf8fec28df73a5e8aba560ec7bb4404be","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:40:04.314408Z","signature_b64":"Rctrw1p99MVZNmbGE6hYn3jiOWtMrxqoed6EbQUxOaFnbZMMK36XTcNsTLD4RRvccA0xKinK+jBzotdhQV15BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"da2799a9c1a5cd0f49e8f9fb43d4364cf8fec28df73a5e8aba560ec7bb4404be","last_reissued_at":"2026-05-18T02:40:04.313964Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:40:04.313964Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1410.3752","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":"2026-05-18T02:40:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H5lE4GgX5LDBU1cKVyKvobLb6amxL9yYZVTEbBdJ5UVNDDhjmZ2cGp8ObGnWWbmjRsDsK+Lpl52/jF/RHh1IBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-24T15:25:00.974406Z"},"content_sha256":"6d69907433377edc4adeca248cf25d0c169ab9e70fbf80782fe6bb84a0336737","schema_version":"1.0","event_id":"sha256:6d69907433377edc4adeca248cf25d0c169ab9e70fbf80782fe6bb84a0336737"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:3ITZTKOBUXGQ6SPI7H5UHVBWJT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Enhanced Random Forest with Image/Patch-Level Learning for Image Understanding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.CV","authors_text":"Chee Seng Chan, Tae-Kyun Kim, Wai Lam Hoo, Yuru Pei","submitted_at":"2014-10-14T16:13:45Z","abstract_excerpt":"Image understanding is an important research domain in the computer vision due to its wide real-world applications. For an image understanding framework that uses the Bag-of-Words model representation, the visual codebook is an essential part. Random forest (RF) as a tree-structure discriminative codebook has been a popular choice. However, the performance of the RF can be degraded if the local patch labels are poorly assigned. In this paper, we tackle this problem by a novel way to update the RF codebook learning for a more discriminative codebook with the introduction of the soft class label"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.3752","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":"2026-05-18T02:40:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dj0wV+/VCh281uXcmgZnnOFQ4y6N+a4XF0KotV7FLBphwedy1Q524cLN5bGhTMYi6RiatnmugqufLcbTVgm6AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-24T15:25:00.975089Z"},"content_sha256":"1c5499c6c7f6c8717e7edc999d5bb31b87b734f880889768800068c38957edd5","schema_version":"1.0","event_id":"sha256:1c5499c6c7f6c8717e7edc999d5bb31b87b734f880889768800068c38957edd5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3ITZTKOBUXGQ6SPI7H5UHVBWJT/bundle.json","state_url":"https://pith.science/pith/3ITZTKOBUXGQ6SPI7H5UHVBWJT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3ITZTKOBUXGQ6SPI7H5UHVBWJT/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":"2026-05-24T15:25:00Z","links":{"resolver":"https://pith.science/pith/3ITZTKOBUXGQ6SPI7H5UHVBWJT","bundle":"https://pith.science/pith/3ITZTKOBUXGQ6SPI7H5UHVBWJT/bundle.json","state":"https://pith.science/pith/3ITZTKOBUXGQ6SPI7H5UHVBWJT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3ITZTKOBUXGQ6SPI7H5UHVBWJT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:3ITZTKOBUXGQ6SPI7H5UHVBWJT","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":"a6d9c9f276c2c30f0675e7c394359e7ae8da8b2a6854e5b65f76fd16b60fd508","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-14T16:13:45Z","title_canon_sha256":"839cf1f7e4954e812e195dd33e9475436ba4ffffff85da3114976c8feb79b3be"},"schema_version":"1.0","source":{"id":"1410.3752","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1410.3752","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"arxiv_version","alias_value":"1410.3752v1","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.3752","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"pith_short_12","alias_value":"3ITZTKOBUXGQ","created_at":"2026-05-18T12:28:11Z"},{"alias_kind":"pith_short_16","alias_value":"3ITZTKOBUXGQ6SPI","created_at":"2026-05-18T12:28:11Z"},{"alias_kind":"pith_short_8","alias_value":"3ITZTKOB","created_at":"2026-05-18T12:28:11Z"}],"graph_snapshots":[{"event_id":"sha256:1c5499c6c7f6c8717e7edc999d5bb31b87b734f880889768800068c38957edd5","target":"graph","created_at":"2026-05-18T02:40:04Z","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":"Image understanding is an important research domain in the computer vision due to its wide real-world applications. For an image understanding framework that uses the Bag-of-Words model representation, the visual codebook is an essential part. Random forest (RF) as a tree-structure discriminative codebook has been a popular choice. However, the performance of the RF can be degraded if the local patch labels are poorly assigned. In this paper, we tackle this problem by a novel way to update the RF codebook learning for a more discriminative codebook with the introduction of the soft class label","authors_text":"Chee Seng Chan, Tae-Kyun Kim, Wai Lam Hoo, Yuru Pei","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-14T16:13:45Z","title":"Enhanced Random Forest with Image/Patch-Level Learning for Image Understanding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.3752","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":"sha256:6d69907433377edc4adeca248cf25d0c169ab9e70fbf80782fe6bb84a0336737","target":"record","created_at":"2026-05-18T02:40:04Z","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":"a6d9c9f276c2c30f0675e7c394359e7ae8da8b2a6854e5b65f76fd16b60fd508","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-14T16:13:45Z","title_canon_sha256":"839cf1f7e4954e812e195dd33e9475436ba4ffffff85da3114976c8feb79b3be"},"schema_version":"1.0","source":{"id":"1410.3752","kind":"arxiv","version":1}},"canonical_sha256":"da2799a9c1a5cd0f49e8f9fb43d4364cf8fec28df73a5e8aba560ec7bb4404be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"da2799a9c1a5cd0f49e8f9fb43d4364cf8fec28df73a5e8aba560ec7bb4404be","first_computed_at":"2026-05-18T02:40:04.313964Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:40:04.313964Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Rctrw1p99MVZNmbGE6hYn3jiOWtMrxqoed6EbQUxOaFnbZMMK36XTcNsTLD4RRvccA0xKinK+jBzotdhQV15BQ==","signature_status":"signed_v1","signed_at":"2026-05-18T02:40:04.314408Z","signed_message":"canonical_sha256_bytes"},"source_id":"1410.3752","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6d69907433377edc4adeca248cf25d0c169ab9e70fbf80782fe6bb84a0336737","sha256:1c5499c6c7f6c8717e7edc999d5bb31b87b734f880889768800068c38957edd5"],"state_sha256":"d976c004ba61d968e471f9646e872ab8ece70156a48d942b6743d123a8a09821"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TmkzoJrkMWfrlEXPhVWpUXlOtvu3bFMTA8HiXh9+6W+RaX72dIXgy5PDHrJ1Fwcy9mORX2rnJtxSQQ9KDi3KAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-24T15:25:00.978753Z","bundle_sha256":"412e66b41161d7defb6df580508e04cce4f5a7d9af79983a993f8a45434618ad"}}