{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:SZSHKE2Z4UZ3WO2D3QEFVDE3WD","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":"4a45b745c112f28cb5ff6bcd310ed4b1cb9413c508c2bf296de7a2cb4d5377f1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-23T05:18:35Z","title_canon_sha256":"172d9035ade133f0d30ddc627d71d4525e5f978f93b718f77e2125e1bc1f5db3"},"schema_version":"1.0","source":{"id":"1802.08290","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.08290","created_at":"2026-05-18T00:18:30Z"},{"alias_kind":"arxiv_version","alias_value":"1802.08290v2","created_at":"2026-05-18T00:18:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.08290","created_at":"2026-05-18T00:18:30Z"},{"alias_kind":"pith_short_12","alias_value":"SZSHKE2Z4UZ3","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_16","alias_value":"SZSHKE2Z4UZ3WO2D","created_at":"2026-05-18T12:32:53Z"},{"alias_kind":"pith_short_8","alias_value":"SZSHKE2Z","created_at":"2026-05-18T12:32:53Z"}],"graph_snapshots":[{"event_id":"sha256:5f776aa23662f4b8810bfc12312fefdd144e656038851e0d603463e97d128733","target":"graph","created_at":"2026-05-18T00:18:30Z","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":"We propose a novel locally adaptive learning estimator for enhancing the inter- and intra- discriminative capabilities of Deep Neural Networks, which can be used as improved loss layer for semantic image segmentation tasks. Most loss layers compute pixel-wise cost between feature maps and ground truths, ignoring spatial layouts and interactions between neighboring pixels with same object category, and thus networks cannot be effectively sensitive to intra-class connections. Stride by stride, our method firstly conducts adaptive pooling filter operating over predicted feature maps, aiming to me","authors_text":"Aiguo Gu, Jian Xu, Jinjiang Guo, Pengyuan Ren, Weixin Wu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-23T05:18:35Z","title":"Locally Adaptive Learning Loss for Semantic Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.08290","kind":"arxiv","version":2},"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:c4c6745ed35db3ca6fe21058ad892357d47e925d1a469316fd8672167c72ed94","target":"record","created_at":"2026-05-18T00:18:30Z","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":"4a45b745c112f28cb5ff6bcd310ed4b1cb9413c508c2bf296de7a2cb4d5377f1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-02-23T05:18:35Z","title_canon_sha256":"172d9035ade133f0d30ddc627d71d4525e5f978f93b718f77e2125e1bc1f5db3"},"schema_version":"1.0","source":{"id":"1802.08290","kind":"arxiv","version":2}},"canonical_sha256":"9664751359e533bb3b43dc085a8c9bb0c39887141c4a9d8e75750b3db18f5033","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9664751359e533bb3b43dc085a8c9bb0c39887141c4a9d8e75750b3db18f5033","first_computed_at":"2026-05-18T00:18:30.954243Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:18:30.954243Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yu3FEsXdB1lQzv45kyeeXKYMtSgj5Aq64SL9VH7m2zUX8wHF0t9OrwunNLHp/LEoNBYlVOuYmwwFD7LO12nhDg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:18:30.954596Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.08290","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4c6745ed35db3ca6fe21058ad892357d47e925d1a469316fd8672167c72ed94","sha256:5f776aa23662f4b8810bfc12312fefdd144e656038851e0d603463e97d128733"],"state_sha256":"52ed2f7a2c54dd9190ce3787d1cb82339f7c04cf5ba2fbf478a41c696b21d490"}