{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:ZPS5V7VJAMNOJHJJTHDRAU4EIC","short_pith_number":"pith:ZPS5V7VJ","canonical_record":{"source":{"id":"1808.00313","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-01T13:37:59Z","cross_cats_sorted":[],"title_canon_sha256":"e1be6d5223ba993c385fe21fcde1430387da3380933311541777d6e8a4efe0cd","abstract_canon_sha256":"71ba711e37ed5b928b6d4e68cc75e2c153b9baa3a730b17f780ffcab90f89001"},"schema_version":"1.0"},"canonical_sha256":"cbe5dafea9031ae49d2999c7105384408c1aca23388477db41ec5a61c57a17ca","source":{"kind":"arxiv","id":"1808.00313","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.00313","created_at":"2026-05-18T00:09:06Z"},{"alias_kind":"arxiv_version","alias_value":"1808.00313v1","created_at":"2026-05-18T00:09:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.00313","created_at":"2026-05-18T00:09:06Z"},{"alias_kind":"pith_short_12","alias_value":"ZPS5V7VJAMNO","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"ZPS5V7VJAMNOJHJJ","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"ZPS5V7VJ","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:ZPS5V7VJAMNOJHJJTHDRAU4EIC","target":"record","payload":{"canonical_record":{"source":{"id":"1808.00313","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-01T13:37:59Z","cross_cats_sorted":[],"title_canon_sha256":"e1be6d5223ba993c385fe21fcde1430387da3380933311541777d6e8a4efe0cd","abstract_canon_sha256":"71ba711e37ed5b928b6d4e68cc75e2c153b9baa3a730b17f780ffcab90f89001"},"schema_version":"1.0"},"canonical_sha256":"cbe5dafea9031ae49d2999c7105384408c1aca23388477db41ec5a61c57a17ca","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:09:06.478881Z","signature_b64":"HVE7a4O5tW2dw2BNdsSA2Dj1T5DpVNfgzHELSX/DhQ8Z66+ZnTnzEPORhzjWs1yqSLYirnbbGamNPAfk37GJDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cbe5dafea9031ae49d2999c7105384408c1aca23388477db41ec5a61c57a17ca","last_reissued_at":"2026-05-18T00:09:06.478332Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:09:06.478332Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.00313","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":"2026-05-18T00:09:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"okMStJ2+OHyOKYFLX223xmykflFTnAKLvGvBHR/GG2y3ReTZ88xpkLG7jBBQXe80eR+1eCshj+BBDZL08t8kDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T11:15:12.619196Z"},"content_sha256":"4bcbc2df26085da7d3104f4d7591371e97b7281bf29b4a7e228349510e557b39","schema_version":"1.0","event_id":"sha256:4bcbc2df26085da7d3104f4d7591371e97b7281bf29b4a7e228349510e557b39"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:ZPS5V7VJAMNOJHJJTHDRAU4EIC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Network Structure to Explicitly Reduce Confusion Errors in Semantic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Qichuan Geng, Ruigang Yang, Xinyu Huang, Zhong Zhou","submitted_at":"2018-08-01T13:37:59Z","abstract_excerpt":"Confusing classes that are ubiquitous in real world often degrade performance for many vision related applications like object detection, classification, and segmentation. The confusion errors are not only caused by similar visual patterns but also amplified by various factors during the training of our designed models, such as reduced feature resolution in the encoding process or imbalanced data distributions. A large amount of deep learning based network structures has been proposed in recent years to deal with these individual factors and improve network performance. However, to our knowled"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.00313","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":"2026-05-18T00:09:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nNunpDmQ0e3A7+hUBdPLMGsoQqoEH6y4tb9cBqMjF06ThPBcCCDrmQBwEcjjF/zEP4h1Hoi7yE9+YLbpkeruAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T11:15:12.619791Z"},"content_sha256":"a0eddd28e11b7c975e7b86d9b45aa6132cd1fa16928e89fdd06cf2fd22f32cdf","schema_version":"1.0","event_id":"sha256:a0eddd28e11b7c975e7b86d9b45aa6132cd1fa16928e89fdd06cf2fd22f32cdf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZPS5V7VJAMNOJHJJTHDRAU4EIC/bundle.json","state_url":"https://pith.science/pith/ZPS5V7VJAMNOJHJJTHDRAU4EIC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZPS5V7VJAMNOJHJJTHDRAU4EIC/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":"2026-05-26T11:15:12Z","links":{"resolver":"https://pith.science/pith/ZPS5V7VJAMNOJHJJTHDRAU4EIC","bundle":"https://pith.science/pith/ZPS5V7VJAMNOJHJJTHDRAU4EIC/bundle.json","state":"https://pith.science/pith/ZPS5V7VJAMNOJHJJTHDRAU4EIC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZPS5V7VJAMNOJHJJTHDRAU4EIC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:ZPS5V7VJAMNOJHJJTHDRAU4EIC","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":"71ba711e37ed5b928b6d4e68cc75e2c153b9baa3a730b17f780ffcab90f89001","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-01T13:37:59Z","title_canon_sha256":"e1be6d5223ba993c385fe21fcde1430387da3380933311541777d6e8a4efe0cd"},"schema_version":"1.0","source":{"id":"1808.00313","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.00313","created_at":"2026-05-18T00:09:06Z"},{"alias_kind":"arxiv_version","alias_value":"1808.00313v1","created_at":"2026-05-18T00:09:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.00313","created_at":"2026-05-18T00:09:06Z"},{"alias_kind":"pith_short_12","alias_value":"ZPS5V7VJAMNO","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"ZPS5V7VJAMNOJHJJ","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"ZPS5V7VJ","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:a0eddd28e11b7c975e7b86d9b45aa6132cd1fa16928e89fdd06cf2fd22f32cdf","target":"graph","created_at":"2026-05-18T00:09:06Z","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":"Confusing classes that are ubiquitous in real world often degrade performance for many vision related applications like object detection, classification, and segmentation. The confusion errors are not only caused by similar visual patterns but also amplified by various factors during the training of our designed models, such as reduced feature resolution in the encoding process or imbalanced data distributions. A large amount of deep learning based network structures has been proposed in recent years to deal with these individual factors and improve network performance. However, to our knowled","authors_text":"Qichuan Geng, Ruigang Yang, Xinyu Huang, Zhong Zhou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-01T13:37:59Z","title":"A Network Structure to Explicitly Reduce Confusion Errors in Semantic Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.00313","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":"sha256:4bcbc2df26085da7d3104f4d7591371e97b7281bf29b4a7e228349510e557b39","target":"record","created_at":"2026-05-18T00:09:06Z","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":"71ba711e37ed5b928b6d4e68cc75e2c153b9baa3a730b17f780ffcab90f89001","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-01T13:37:59Z","title_canon_sha256":"e1be6d5223ba993c385fe21fcde1430387da3380933311541777d6e8a4efe0cd"},"schema_version":"1.0","source":{"id":"1808.00313","kind":"arxiv","version":1}},"canonical_sha256":"cbe5dafea9031ae49d2999c7105384408c1aca23388477db41ec5a61c57a17ca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cbe5dafea9031ae49d2999c7105384408c1aca23388477db41ec5a61c57a17ca","first_computed_at":"2026-05-18T00:09:06.478332Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:09:06.478332Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HVE7a4O5tW2dw2BNdsSA2Dj1T5DpVNfgzHELSX/DhQ8Z66+ZnTnzEPORhzjWs1yqSLYirnbbGamNPAfk37GJDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:09:06.478881Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.00313","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4bcbc2df26085da7d3104f4d7591371e97b7281bf29b4a7e228349510e557b39","sha256:a0eddd28e11b7c975e7b86d9b45aa6132cd1fa16928e89fdd06cf2fd22f32cdf"],"state_sha256":"c5a0c142cb40765ce27c3a2bacaad1383a57d730692126134bba6d0c8207f3fb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"U6bZT5e7cntnEz8JKSd8JOmbH8OejsTs7ow3TVPtfwzwVCjyvsKaiYJeTtTTyQ1cA/u0CO4TGcSS8Q0C5HCMDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T11:15:12.623095Z","bundle_sha256":"3b78e3ab234a24b5cec509d043ba4bccff04f05c6bf8a32629e76430fee9a973"}}