{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:2NJDJMXCEL73ZVOPZ3BTJCVTLD","short_pith_number":"pith:2NJDJMXC","schema_version":"1.0","canonical_sha256":"d35234b2e222ffbcd5cfcec3348ab358dd1619d97b75d41a02e5ead0a809e0b8","source":{"kind":"arxiv","id":"2203.12469","version":1},"attestation_state":"computed","paper":{"title":"3D Adapted Random Forest Vision (3DARFV) for Untangling Heterogeneous-Fabric Exceeding Deep Learning Semantic Segmentation Efficiency at the Utmost Accuracy","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM","cs.LG","eess.IV","physics.geo-ph"],"primary_cat":"cs.CV","authors_text":"Anthony Tzes, Ashraf Al-Khateeb, Haifa Alyazeedi, Hamed Alhashmi, Mohamed Abdelsalam, Omar Alfarisi, Qingfeng Huang, Salem Alzaabi, Zeyar Aung","submitted_at":"2022-03-23T15:05:23Z","abstract_excerpt":"Planetary exploration depends heavily on 3D image data to characterize the static and dynamic properties of the rock and environment. Analyzing 3D images requires many computations, causing efficiency to suffer lengthy processing time alongside large energy consumption. High-Performance Computing (HPC) provides apparent efficiency at the expense of energy consumption. However, for remote explorations, the conveyed surveillance and the robotized sensing need faster data analysis with ultimate accuracy to make real-time decisions. In such environments, access to HPC and energy is limited. Theref"},"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":"2203.12469","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-03-23T15:05:23Z","cross_cats_sorted":["astro-ph.IM","cs.LG","eess.IV","physics.geo-ph"],"title_canon_sha256":"efcc312c649b15e9831c056fed5452fab3ea861e5caf266d8a5a2e3f97163206","abstract_canon_sha256":"cb20f6e229840bd6a67044d75be2b05b42c8ea8c5a004fee38d27a5fb77067e2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:13:14.256137Z","signature_b64":"MKg0msZ6GwJwurmzOsw6V2i/a7dgUBPbC5inixb0sMO7L3gLb7+RfSz/sXBHIUpmOpfpS1KXVYd86HvrVka/BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d35234b2e222ffbcd5cfcec3348ab358dd1619d97b75d41a02e5ead0a809e0b8","last_reissued_at":"2026-07-05T04:13:14.255668Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:13:14.255668Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"3D Adapted Random Forest Vision (3DARFV) for Untangling Heterogeneous-Fabric Exceeding Deep Learning Semantic Segmentation Efficiency at the Utmost Accuracy","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM","cs.LG","eess.IV","physics.geo-ph"],"primary_cat":"cs.CV","authors_text":"Anthony Tzes, Ashraf Al-Khateeb, Haifa Alyazeedi, Hamed Alhashmi, Mohamed Abdelsalam, Omar Alfarisi, Qingfeng Huang, Salem Alzaabi, Zeyar Aung","submitted_at":"2022-03-23T15:05:23Z","abstract_excerpt":"Planetary exploration depends heavily on 3D image data to characterize the static and dynamic properties of the rock and environment. Analyzing 3D images requires many computations, causing efficiency to suffer lengthy processing time alongside large energy consumption. High-Performance Computing (HPC) provides apparent efficiency at the expense of energy consumption. However, for remote explorations, the conveyed surveillance and the robotized sensing need faster data analysis with ultimate accuracy to make real-time decisions. In such environments, access to HPC and energy is limited. Theref"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.12469","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2203.12469/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2203.12469","created_at":"2026-07-05T04:13:14.255731+00:00"},{"alias_kind":"arxiv_version","alias_value":"2203.12469v1","created_at":"2026-07-05T04:13:14.255731+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.12469","created_at":"2026-07-05T04:13:14.255731+00:00"},{"alias_kind":"pith_short_12","alias_value":"2NJDJMXCEL73","created_at":"2026-07-05T04:13:14.255731+00:00"},{"alias_kind":"pith_short_16","alias_value":"2NJDJMXCEL73ZVOP","created_at":"2026-07-05T04:13:14.255731+00:00"},{"alias_kind":"pith_short_8","alias_value":"2NJDJMXC","created_at":"2026-07-05T04:13:14.255731+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/2NJDJMXCEL73ZVOPZ3BTJCVTLD","json":"https://pith.science/pith/2NJDJMXCEL73ZVOPZ3BTJCVTLD.json","graph_json":"https://pith.science/api/pith-number/2NJDJMXCEL73ZVOPZ3BTJCVTLD/graph.json","events_json":"https://pith.science/api/pith-number/2NJDJMXCEL73ZVOPZ3BTJCVTLD/events.json","paper":"https://pith.science/paper/2NJDJMXC"},"agent_actions":{"view_html":"https://pith.science/pith/2NJDJMXCEL73ZVOPZ3BTJCVTLD","download_json":"https://pith.science/pith/2NJDJMXCEL73ZVOPZ3BTJCVTLD.json","view_paper":"https://pith.science/paper/2NJDJMXC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2203.12469&json=true","fetch_graph":"https://pith.science/api/pith-number/2NJDJMXCEL73ZVOPZ3BTJCVTLD/graph.json","fetch_events":"https://pith.science/api/pith-number/2NJDJMXCEL73ZVOPZ3BTJCVTLD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2NJDJMXCEL73ZVOPZ3BTJCVTLD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2NJDJMXCEL73ZVOPZ3BTJCVTLD/action/storage_attestation","attest_author":"https://pith.science/pith/2NJDJMXCEL73ZVOPZ3BTJCVTLD/action/author_attestation","sign_citation":"https://pith.science/pith/2NJDJMXCEL73ZVOPZ3BTJCVTLD/action/citation_signature","submit_replication":"https://pith.science/pith/2NJDJMXCEL73ZVOPZ3BTJCVTLD/action/replication_record"}},"created_at":"2026-07-05T04:13:14.255731+00:00","updated_at":"2026-07-05T04:13:14.255731+00:00"}