{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:UAJFBAGV7BRC3H7KIWZRCSX55Z","short_pith_number":"pith:UAJFBAGV","canonical_record":{"source":{"id":"2408.06467","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-12T19:42:09Z","cross_cats_sorted":[],"title_canon_sha256":"fe5151b5b0b04809178872aa7c7064a2d0319f99df80ba51eb95d9680ed22284","abstract_canon_sha256":"18bcbf8973b9b7b3489cbb72fd62480f9de59d14dd39fbbfb9e6ed664c4fac46"},"schema_version":"1.0"},"canonical_sha256":"a0125080d5f8622d9fea45b3114afdee7da7cbf075519a27440361be9a3a4c77","source":{"kind":"arxiv","id":"2408.06467","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.06467","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"arxiv_version","alias_value":"2408.06467v2","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.06467","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_12","alias_value":"UAJFBAGV7BRC","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_16","alias_value":"UAJFBAGV7BRC3H7K","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_8","alias_value":"UAJFBAGV","created_at":"2026-07-05T08:56:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:UAJFBAGV7BRC3H7KIWZRCSX55Z","target":"record","payload":{"canonical_record":{"source":{"id":"2408.06467","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-12T19:42:09Z","cross_cats_sorted":[],"title_canon_sha256":"fe5151b5b0b04809178872aa7c7064a2d0319f99df80ba51eb95d9680ed22284","abstract_canon_sha256":"18bcbf8973b9b7b3489cbb72fd62480f9de59d14dd39fbbfb9e6ed664c4fac46"},"schema_version":"1.0"},"canonical_sha256":"a0125080d5f8622d9fea45b3114afdee7da7cbf075519a27440361be9a3a4c77","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:56:05.819230Z","signature_b64":"WrehjhxcGU3fWXKPVnLV/C/IbssIUqqAS7FbdRZL+XATq7sVHBpvBfrknXeEvQTx0YK5wpP32TDGRYyrNqIeBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a0125080d5f8622d9fea45b3114afdee7da7cbf075519a27440361be9a3a4c77","last_reissued_at":"2026-07-05T08:56:05.818757Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:56:05.818757Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.06467","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:56:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mOyypiIDwyImrcgftOy3vze94mgHb3F71OOu0xAdxN1Vth+aosK7hPovA3w35yNapGan0VmqeGkXQ6AsrSI+AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-18T10:10:15.320620Z"},"content_sha256":"eab638c7efecd67d740f2778d00a4a60ec41bad68aa8a87c2b9b48d569bc8f62","schema_version":"1.0","event_id":"sha256:eab638c7efecd67d740f2778d00a4a60ec41bad68aa8a87c2b9b48d569bc8f62"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:UAJFBAGV7BRC3H7KIWZRCSX55Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generalization Enhancement Strategies to Enable Cross-year Cropland Mapping with Convolutional Neural Networks Trained Using Historical Samples","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amos Wussah, Boka Luo, Cat Mai, Hamed Alemohammad, Hanan Abou Ali, Ismail Alatise, Lei Song, Lyndon D. Estes, Mary Dziedzorm Asipunu, Nguyen Ha, Qi Zhang, Rahebe Abedi, Sam Khallaghi, Sitian Xiong, Yao-Ting Yao","submitted_at":"2024-08-12T19:42:09Z","abstract_excerpt":"The accuracy of mapping agricultural fields across large areas is steadily improving with high-resolution satellite imagery and deep learning (DL) models, even in regions where fields are small and geometrically irregular. However, developing effective DL models often requires large, expensive label datasets, typically available only for specific years or locations. This limits the ability to create annual maps essential for agricultural monitoring, as domain shifts occur between years and regions due to changes in farming practices and environmental conditions. The challenge is to design a mo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.06467","kind":"arxiv","version":2},"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/2408.06467/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:56:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YoX/6kqYNKUg9+e5l48Alc8Nnie36mfutfbhg22OrLFDAwf4FK14xfg3oFHioOs/V8gWXggT5l3Hi8UTQii2CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-18T10:10:15.320983Z"},"content_sha256":"ff74041bff14c87349898c56ed977421abaa7388753cc418c7ae2f13b554d282","schema_version":"1.0","event_id":"sha256:ff74041bff14c87349898c56ed977421abaa7388753cc418c7ae2f13b554d282"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UAJFBAGV7BRC3H7KIWZRCSX55Z/bundle.json","state_url":"https://pith.science/pith/UAJFBAGV7BRC3H7KIWZRCSX55Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UAJFBAGV7BRC3H7KIWZRCSX55Z/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-18T10:10:15Z","links":{"resolver":"https://pith.science/pith/UAJFBAGV7BRC3H7KIWZRCSX55Z","bundle":"https://pith.science/pith/UAJFBAGV7BRC3H7KIWZRCSX55Z/bundle.json","state":"https://pith.science/pith/UAJFBAGV7BRC3H7KIWZRCSX55Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UAJFBAGV7BRC3H7KIWZRCSX55Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:UAJFBAGV7BRC3H7KIWZRCSX55Z","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":"18bcbf8973b9b7b3489cbb72fd62480f9de59d14dd39fbbfb9e6ed664c4fac46","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-12T19:42:09Z","title_canon_sha256":"fe5151b5b0b04809178872aa7c7064a2d0319f99df80ba51eb95d9680ed22284"},"schema_version":"1.0","source":{"id":"2408.06467","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.06467","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"arxiv_version","alias_value":"2408.06467v2","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.06467","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_12","alias_value":"UAJFBAGV7BRC","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_16","alias_value":"UAJFBAGV7BRC3H7K","created_at":"2026-07-05T08:56:05Z"},{"alias_kind":"pith_short_8","alias_value":"UAJFBAGV","created_at":"2026-07-05T08:56:05Z"}],"graph_snapshots":[{"event_id":"sha256:ff74041bff14c87349898c56ed977421abaa7388753cc418c7ae2f13b554d282","target":"graph","created_at":"2026-07-05T08:56:05Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2408.06467/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The accuracy of mapping agricultural fields across large areas is steadily improving with high-resolution satellite imagery and deep learning (DL) models, even in regions where fields are small and geometrically irregular. However, developing effective DL models often requires large, expensive label datasets, typically available only for specific years or locations. This limits the ability to create annual maps essential for agricultural monitoring, as domain shifts occur between years and regions due to changes in farming practices and environmental conditions. The challenge is to design a mo","authors_text":"Amos Wussah, Boka Luo, Cat Mai, Hamed Alemohammad, Hanan Abou Ali, Ismail Alatise, Lei Song, Lyndon D. Estes, Mary Dziedzorm Asipunu, Nguyen Ha, Qi Zhang, Rahebe Abedi, Sam Khallaghi, Sitian Xiong, Yao-Ting Yao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-12T19:42:09Z","title":"Generalization Enhancement Strategies to Enable Cross-year Cropland Mapping with Convolutional Neural Networks Trained Using Historical Samples"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.06467","kind":"arxiv","version":2},"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:eab638c7efecd67d740f2778d00a4a60ec41bad68aa8a87c2b9b48d569bc8f62","target":"record","created_at":"2026-07-05T08:56:05Z","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":"18bcbf8973b9b7b3489cbb72fd62480f9de59d14dd39fbbfb9e6ed664c4fac46","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-12T19:42:09Z","title_canon_sha256":"fe5151b5b0b04809178872aa7c7064a2d0319f99df80ba51eb95d9680ed22284"},"schema_version":"1.0","source":{"id":"2408.06467","kind":"arxiv","version":2}},"canonical_sha256":"a0125080d5f8622d9fea45b3114afdee7da7cbf075519a27440361be9a3a4c77","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a0125080d5f8622d9fea45b3114afdee7da7cbf075519a27440361be9a3a4c77","first_computed_at":"2026-07-05T08:56:05.818757Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:56:05.818757Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WrehjhxcGU3fWXKPVnLV/C/IbssIUqqAS7FbdRZL+XATq7sVHBpvBfrknXeEvQTx0YK5wpP32TDGRYyrNqIeBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:56:05.819230Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.06467","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eab638c7efecd67d740f2778d00a4a60ec41bad68aa8a87c2b9b48d569bc8f62","sha256:ff74041bff14c87349898c56ed977421abaa7388753cc418c7ae2f13b554d282"],"state_sha256":"e775c236f3692c04643a9d612196945d889b326804adf4ab9713284e4afcc595"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T7IcnsWPPIe7j7G+QaukXNuAsoIPF4ogyN/Q37DXqDIMirOaAYononFb/OFJFpzvsFTNNMRu+6vIteA9XWInBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-18T10:10:15.323125Z","bundle_sha256":"2802556d948be96da1506040003228478ca356fa384de16793e6cfe2a34efaaa"}}