{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:ACYJHLOZUJ7YR75FYS3OIYGCPF","short_pith_number":"pith:ACYJHLOZ","schema_version":"1.0","canonical_sha256":"00b093add9a27f88ffa5c4b6e460c27968755c1b7f6eabb97f3c163fd3aefa47","source":{"kind":"arxiv","id":"1707.09099","version":1},"attestation_state":"computed","paper":{"title":"Object Detection of Satellite Images Using Multi-Channel Higher-order Local Autocorrelation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hidenori Sakanashi, Hirokazu Nosato, Hiroki Miyamoto, Kazuki Uehara, Masahiro Murakawa, Ryosuke Nakamura","submitted_at":"2017-07-28T03:59:27Z","abstract_excerpt":"The Earth observation satellites have been monitoring the earth's surface for a long time, and the images taken by the satellites contain large amounts of valuable data. However, it is extremely hard work to manually analyze such huge data. Thus, a method of automatic object detection is needed for satellite images to facilitate efficient data analyses. This paper describes a new image feature extended from higher-order local autocorrelation to the object detection of multispectral satellite images. The feature has been extended to extract spectral inter-relationships in addition to spatial re"},"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":"1707.09099","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-07-28T03:59:27Z","cross_cats_sorted":[],"title_canon_sha256":"94a93c4f696260de40e4a4d67eb481f1c2f658d01a8e6ca4790e957e5f5ef513","abstract_canon_sha256":"b38b7cd5fbe1d522c988f74c2209fbf331c19d0b1d7f17575d5a6b23046bfee6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:17.093703Z","signature_b64":"geDycJuLQ35o6KoQHCqL69+Oiohhel7F3rYjJ4vGmU21uyKgFCLGKsy05jcDObErxxpQdPBTIyvCfG7GaCQjBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"00b093add9a27f88ffa5c4b6e460c27968755c1b7f6eabb97f3c163fd3aefa47","last_reissued_at":"2026-05-18T00:39:17.093114Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:17.093114Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Object Detection of Satellite Images Using Multi-Channel Higher-order Local Autocorrelation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hidenori Sakanashi, Hirokazu Nosato, Hiroki Miyamoto, Kazuki Uehara, Masahiro Murakawa, Ryosuke Nakamura","submitted_at":"2017-07-28T03:59:27Z","abstract_excerpt":"The Earth observation satellites have been monitoring the earth's surface for a long time, and the images taken by the satellites contain large amounts of valuable data. However, it is extremely hard work to manually analyze such huge data. Thus, a method of automatic object detection is needed for satellite images to facilitate efficient data analyses. This paper describes a new image feature extended from higher-order local autocorrelation to the object detection of multispectral satellite images. The feature has been extended to extract spectral inter-relationships in addition to spatial re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.09099","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":"1707.09099","created_at":"2026-05-18T00:39:17.093204+00:00"},{"alias_kind":"arxiv_version","alias_value":"1707.09099v1","created_at":"2026-05-18T00:39:17.093204+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.09099","created_at":"2026-05-18T00:39:17.093204+00:00"},{"alias_kind":"pith_short_12","alias_value":"ACYJHLOZUJ7Y","created_at":"2026-05-18T12:31:05.417338+00:00"},{"alias_kind":"pith_short_16","alias_value":"ACYJHLOZUJ7YR75F","created_at":"2026-05-18T12:31:05.417338+00:00"},{"alias_kind":"pith_short_8","alias_value":"ACYJHLOZ","created_at":"2026-05-18T12:31:05.417338+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/ACYJHLOZUJ7YR75FYS3OIYGCPF","json":"https://pith.science/pith/ACYJHLOZUJ7YR75FYS3OIYGCPF.json","graph_json":"https://pith.science/api/pith-number/ACYJHLOZUJ7YR75FYS3OIYGCPF/graph.json","events_json":"https://pith.science/api/pith-number/ACYJHLOZUJ7YR75FYS3OIYGCPF/events.json","paper":"https://pith.science/paper/ACYJHLOZ"},"agent_actions":{"view_html":"https://pith.science/pith/ACYJHLOZUJ7YR75FYS3OIYGCPF","download_json":"https://pith.science/pith/ACYJHLOZUJ7YR75FYS3OIYGCPF.json","view_paper":"https://pith.science/paper/ACYJHLOZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1707.09099&json=true","fetch_graph":"https://pith.science/api/pith-number/ACYJHLOZUJ7YR75FYS3OIYGCPF/graph.json","fetch_events":"https://pith.science/api/pith-number/ACYJHLOZUJ7YR75FYS3OIYGCPF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ACYJHLOZUJ7YR75FYS3OIYGCPF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ACYJHLOZUJ7YR75FYS3OIYGCPF/action/storage_attestation","attest_author":"https://pith.science/pith/ACYJHLOZUJ7YR75FYS3OIYGCPF/action/author_attestation","sign_citation":"https://pith.science/pith/ACYJHLOZUJ7YR75FYS3OIYGCPF/action/citation_signature","submit_replication":"https://pith.science/pith/ACYJHLOZUJ7YR75FYS3OIYGCPF/action/replication_record"}},"created_at":"2026-05-18T00:39:17.093204+00:00","updated_at":"2026-05-18T00:39:17.093204+00:00"}