{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:2TC5E547UWTW334OGHMVONCTYN","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":"f9d3c233c3f94c3bb33f5ef6e3579486ff3c77d9329cc27810f249ec826ff245","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-27T15:32:10Z","title_canon_sha256":"8ef28ba8c2dd3a8f398c7e43e4afaad117dcf1ee69efeb9f2c23c9a6743ca024"},"schema_version":"1.0","source":{"id":"1907.11935","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.11935","created_at":"2026-05-17T23:39:22Z"},{"alias_kind":"arxiv_version","alias_value":"1907.11935v1","created_at":"2026-05-17T23:39:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.11935","created_at":"2026-05-17T23:39:22Z"},{"alias_kind":"pith_short_12","alias_value":"2TC5E547UWTW","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"2TC5E547UWTW334O","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"2TC5E547","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:4f23bbece75fa9cc5fe8573b08a3a2e1f51ff49f65ddd5c7627c9849a40e3861","target":"graph","created_at":"2026-05-17T23:39:22Z","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":"Hyperspectral imaging provides detailed information about the scanned objects, as it captures their spectral characteristics within a large number of wavelength bands. Classification of such data has become an active research topic due to its wide applicability in a variety of fields. Deep learning has established the state of the art in the area, and it constitutes the current research mainstream. In this letter, we introduce a new spectral-spatial convolutional neural network, benefitting from a battery of data augmentation techniques which help deal with a real-life problem of lacking groun","authors_text":"Jakub Nalepa, Lukasz Tulczyjew, Michal Kawulok, Michal Myller","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-27T15:32:10Z","title":"Segmenting Hyperspectral Images Using Spectral-Spatial Convolutional Neural Networks With Training-Time Data Augmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.11935","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:f8b4b6c30052a73c2b343988c3af788560a0c4e8923afbbe4ef9f42f6db6f045","target":"record","created_at":"2026-05-17T23:39:22Z","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":"f9d3c233c3f94c3bb33f5ef6e3579486ff3c77d9329cc27810f249ec826ff245","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-27T15:32:10Z","title_canon_sha256":"8ef28ba8c2dd3a8f398c7e43e4afaad117dcf1ee69efeb9f2c23c9a6743ca024"},"schema_version":"1.0","source":{"id":"1907.11935","kind":"arxiv","version":1}},"canonical_sha256":"d4c5d2779fa5a76def8e31d9573453c361b2710b0ce62f7330f5fb8672de5cc8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d4c5d2779fa5a76def8e31d9573453c361b2710b0ce62f7330f5fb8672de5cc8","first_computed_at":"2026-05-17T23:39:22.465862Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:39:22.465862Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MbvwcgvthCh/+0aZiEpammp5gRrCP0k5B0SxxS+o3Qyx5oJljJJc7MRCQfeppisEZ3+BBXeCH9RdWnaAwP36DQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:39:22.466653Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.11935","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f8b4b6c30052a73c2b343988c3af788560a0c4e8923afbbe4ef9f42f6db6f045","sha256:4f23bbece75fa9cc5fe8573b08a3a2e1f51ff49f65ddd5c7627c9849a40e3861"],"state_sha256":"daf3cef48c9b5e80b39fe75f5d2ac2fb638a7f8ced259f1acd96c0dad2d98423"}