{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:3NESH4XXMUW4HKTQHSHSL4IBQX","short_pith_number":"pith:3NESH4XX","schema_version":"1.0","canonical_sha256":"db4923f2f7652dc3aa703c8f25f10185e668b556792cf070b956cf16ebcee21a","source":{"kind":"arxiv","id":"1410.2188","version":1},"attestation_state":"computed","paper":{"title":"An Aerial Image Recognition Framework using Discrimination and Redundancy Quality Measure","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Luming Zhang, Yuxin Hu","submitted_at":"2014-10-06T16:40:02Z","abstract_excerpt":"Aerial image categorization plays an indispensable role in remote sensing and artificial intelligence. In this paper, we propose a new aerial image categorization framework, focusing on organizing the local patches of each aerial image into multiple discriminative subgraphs. The subgraphs reflect both the geometric property and the color distribution of an aerial image. First, each aerial image is decomposed into a collection of regions in terms of their color intensities. Thereby region connected graph (RCG), which models the connection between the spatial neighboring regions, is constructed "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1410.2188","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-06T16:40:02Z","cross_cats_sorted":[],"title_canon_sha256":"19a7ecdc4e715b21982fb3199152d5185da16d98ddfbd92de55615482c9c1af9","abstract_canon_sha256":"ecd27ae6259ab2f271c013a15a163f4c49744731082da3de8650ef195cc1c45c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:00:20.254222Z","signature_b64":"tBrWQ/3UqS1Q52aO0E80jEHBVWkAnK/S6J1gij5TTqATZjiiMHHS/URcDXkH7EA3pLYj18KqLmpqcSBzIo2cBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"db4923f2f7652dc3aa703c8f25f10185e668b556792cf070b956cf16ebcee21a","last_reissued_at":"2026-05-18T01:00:20.253530Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:00:20.253530Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"An Aerial Image Recognition Framework using Discrimination and Redundancy Quality Measure","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Luming Zhang, Yuxin Hu","submitted_at":"2014-10-06T16:40:02Z","abstract_excerpt":"Aerial image categorization plays an indispensable role in remote sensing and artificial intelligence. In this paper, we propose a new aerial image categorization framework, focusing on organizing the local patches of each aerial image into multiple discriminative subgraphs. The subgraphs reflect both the geometric property and the color distribution of an aerial image. First, each aerial image is decomposed into a collection of regions in terms of their color intensities. Thereby region connected graph (RCG), which models the connection between the spatial neighboring regions, is constructed "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.2188","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1410.2188","created_at":"2026-05-18T01:00:20.253633+00:00"},{"alias_kind":"arxiv_version","alias_value":"1410.2188v1","created_at":"2026-05-18T01:00:20.253633+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.2188","created_at":"2026-05-18T01:00:20.253633+00:00"},{"alias_kind":"pith_short_12","alias_value":"3NESH4XXMUW4","created_at":"2026-05-18T12:28:11.866339+00:00"},{"alias_kind":"pith_short_16","alias_value":"3NESH4XXMUW4HKTQ","created_at":"2026-05-18T12:28:11.866339+00:00"},{"alias_kind":"pith_short_8","alias_value":"3NESH4XX","created_at":"2026-05-18T12:28:11.866339+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/3NESH4XXMUW4HKTQHSHSL4IBQX","json":"https://pith.science/pith/3NESH4XXMUW4HKTQHSHSL4IBQX.json","graph_json":"https://pith.science/api/pith-number/3NESH4XXMUW4HKTQHSHSL4IBQX/graph.json","events_json":"https://pith.science/api/pith-number/3NESH4XXMUW4HKTQHSHSL4IBQX/events.json","paper":"https://pith.science/paper/3NESH4XX"},"agent_actions":{"view_html":"https://pith.science/pith/3NESH4XXMUW4HKTQHSHSL4IBQX","download_json":"https://pith.science/pith/3NESH4XXMUW4HKTQHSHSL4IBQX.json","view_paper":"https://pith.science/paper/3NESH4XX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1410.2188&json=true","fetch_graph":"https://pith.science/api/pith-number/3NESH4XXMUW4HKTQHSHSL4IBQX/graph.json","fetch_events":"https://pith.science/api/pith-number/3NESH4XXMUW4HKTQHSHSL4IBQX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3NESH4XXMUW4HKTQHSHSL4IBQX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3NESH4XXMUW4HKTQHSHSL4IBQX/action/storage_attestation","attest_author":"https://pith.science/pith/3NESH4XXMUW4HKTQHSHSL4IBQX/action/author_attestation","sign_citation":"https://pith.science/pith/3NESH4XXMUW4HKTQHSHSL4IBQX/action/citation_signature","submit_replication":"https://pith.science/pith/3NESH4XXMUW4HKTQHSHSL4IBQX/action/replication_record"}},"created_at":"2026-05-18T01:00:20.253633+00:00","updated_at":"2026-05-18T01:00:20.253633+00:00"}