{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:Z27HGMYVXZVBDB6AC3EQCFE2WF","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":"8447a3bcd7c51c4cc052c004f285d4f8b59ee925429e94d74ef37cb0aba72888","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T04:52:19Z","title_canon_sha256":"98ed98a365174e348743f058dcf036581ee13bacf4cecd4e86051eac16d678a0"},"schema_version":"1.0","source":{"id":"1904.07461","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.07461","created_at":"2026-05-17T23:48:25Z"},{"alias_kind":"arxiv_version","alias_value":"1904.07461v1","created_at":"2026-05-17T23:48:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.07461","created_at":"2026-05-17T23:48:25Z"},{"alias_kind":"pith_short_12","alias_value":"Z27HGMYVXZVB","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"Z27HGMYVXZVBDB6A","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"Z27HGMYV","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:148d749224f87e0f7c68b8cc5e086fddac94331d7fc23e9eb2f745c802301858","target":"graph","created_at":"2026-05-17T23:48:25Z","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 learning has been widely used for hyperspectral pixel classification due to its ability of generating deep feature representation. However, how to construct an efficient and powerful network suitable for hyperspectral data is still under exploration. In this paper, a novel neural network model is designed for taking full advantage of the spectral-spatial structure of hyperspectral data. Firstly, we extract pixel-based intrinsic features from rich yet redundant spectral bands by a subnetwork with supervised pre-training scheme. Secondly, in order to utilize the local spatial correlation am","authors_text":"Jingzhou Chen, Peilin Zhou, Siyu Chen, Yuntao Qian","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T04:52:19Z","title":"Deep Neural Network Based Hyperspectral Pixel Classification With Factorized Spectral-Spatial Feature Representation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.07461","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":"sha256:37285278801bb5043da0f9d451aa4fd414bb3dc014e93919248952f45d09b19f","target":"record","created_at":"2026-05-17T23:48:25Z","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":"8447a3bcd7c51c4cc052c004f285d4f8b59ee925429e94d74ef37cb0aba72888","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T04:52:19Z","title_canon_sha256":"98ed98a365174e348743f058dcf036581ee13bacf4cecd4e86051eac16d678a0"},"schema_version":"1.0","source":{"id":"1904.07461","kind":"arxiv","version":1}},"canonical_sha256":"cebe733315be6a1187c016c901149ab17b9fe102da293fc60258c69609629a97","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cebe733315be6a1187c016c901149ab17b9fe102da293fc60258c69609629a97","first_computed_at":"2026-05-17T23:48:25.186272Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:25.186272Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kBLQigT/7KwK9eeeR9/cYgsKuuOl7FUJGS60jN76EL8PBSou2JJ2fRxEf8snXyRM42baQH9Diad+j9qDJ14aDg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:25.186818Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.07461","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:37285278801bb5043da0f9d451aa4fd414bb3dc014e93919248952f45d09b19f","sha256:148d749224f87e0f7c68b8cc5e086fddac94331d7fc23e9eb2f745c802301858"],"state_sha256":"dcec891785aa5123f45ed9e4862bb704bf115897ffdbb3b9ee94cf74a1511362"}