{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:LEEXS4OHWDGTOOXOZISGOOHIZS","short_pith_number":"pith:LEEXS4OH","canonical_record":{"source":{"id":"2204.08271","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-04-18T12:11:15Z","cross_cats_sorted":[],"title_canon_sha256":"11030aac908a521928915d67ae2c6bf47b1d734ec446ddaec68b6109394ca252","abstract_canon_sha256":"97589f3b1b9438d8fd095af761c7558bf6bbfa6d71f114612f27aa8457eec210"},"schema_version":"1.0"},"canonical_sha256":"59097971c7b0cd373aeeca246738e8cc8b376ad1cca343dd506738c66ab4b84e","source":{"kind":"arxiv","id":"2204.08271","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2204.08271","created_at":"2026-07-05T04:15:24Z"},{"alias_kind":"arxiv_version","alias_value":"2204.08271v1","created_at":"2026-07-05T04:15:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.08271","created_at":"2026-07-05T04:15:24Z"},{"alias_kind":"pith_short_12","alias_value":"LEEXS4OHWDGT","created_at":"2026-07-05T04:15:24Z"},{"alias_kind":"pith_short_16","alias_value":"LEEXS4OHWDGTOOXO","created_at":"2026-07-05T04:15:24Z"},{"alias_kind":"pith_short_8","alias_value":"LEEXS4OH","created_at":"2026-07-05T04:15:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:LEEXS4OHWDGTOOXOZISGOOHIZS","target":"record","payload":{"canonical_record":{"source":{"id":"2204.08271","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-04-18T12:11:15Z","cross_cats_sorted":[],"title_canon_sha256":"11030aac908a521928915d67ae2c6bf47b1d734ec446ddaec68b6109394ca252","abstract_canon_sha256":"97589f3b1b9438d8fd095af761c7558bf6bbfa6d71f114612f27aa8457eec210"},"schema_version":"1.0"},"canonical_sha256":"59097971c7b0cd373aeeca246738e8cc8b376ad1cca343dd506738c66ab4b84e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:15:24.160172Z","signature_b64":"zYcp6RTlbJXgWALEOidSAfI3d1rPuuxz8KGgd8MZwNnTAAv5g0/3AZzFD0D6VNNPFpIPk2bCnhiSG5vDHDJ3BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59097971c7b0cd373aeeca246738e8cc8b376ad1cca343dd506738c66ab4b84e","last_reissued_at":"2026-07-05T04:15:24.159699Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:15:24.159699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2204.08271","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:15:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q1K+42CXVnTsXnJuOCwu0W519SQWFt8CouXgsgCm4QK8VBe+x/DETUsP4I1WJ/m74YN4ereR8rMUYFTHozceCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T23:19:19.664289Z"},"content_sha256":"3e96be02a2703e7a6f41a2bc825b69754b2ba1abcc53268ed08498303c051d8e","schema_version":"1.0","event_id":"sha256:3e96be02a2703e7a6f41a2bc825b69754b2ba1abcc53268ed08498303c051d8e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:LEEXS4OHWDGTOOXOZISGOOHIZS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Badri Narayanan, Brian Mac Namee, Deirdre Hennessey, Jaime Fernandez, Kevin McGuinness, Mohamed Saadeldin, Noel E. O'Connor, Paul Albert","submitted_at":"2022-04-18T12:11:15Z","abstract_excerpt":"Herbage mass yield and composition estimation is an important tool for dairy farmers to ensure an adequate supply of high quality herbage for grazing and subsequently milk production. By accurately estimating herbage mass and composition, targeted nitrogen fertiliser application strategies can be deployed to improve localised regions in a herbage field, effectively reducing the negative impacts of over-fertilization on biodiversity and the environment. In this context, deep learning algorithms offer a tempting alternative to the usual means of sward composition estimation, which involves the d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.08271","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/2204.08271/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":"2026-07-05T04:15:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XvwF6DeVzzSk161HBCbND59/7J0jWYcJS6m6rk5cCxjKknfQZr52BVogcVEwaGMbjITlh4KcBtIdWOISzJLoDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T23:19:19.664809Z"},"content_sha256":"9b9dc7b368f11aa0d66a7490e4ea98550f66e33b8d6f2bdb3b009e84b1fab32c","schema_version":"1.0","event_id":"sha256:9b9dc7b368f11aa0d66a7490e4ea98550f66e33b8d6f2bdb3b009e84b1fab32c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LEEXS4OHWDGTOOXOZISGOOHIZS/bundle.json","state_url":"https://pith.science/pith/LEEXS4OHWDGTOOXOZISGOOHIZS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LEEXS4OHWDGTOOXOZISGOOHIZS/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":"2026-08-10T23:19:19Z","links":{"resolver":"https://pith.science/pith/LEEXS4OHWDGTOOXOZISGOOHIZS","bundle":"https://pith.science/pith/LEEXS4OHWDGTOOXOZISGOOHIZS/bundle.json","state":"https://pith.science/pith/LEEXS4OHWDGTOOXOZISGOOHIZS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LEEXS4OHWDGTOOXOZISGOOHIZS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:LEEXS4OHWDGTOOXOZISGOOHIZS","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":"97589f3b1b9438d8fd095af761c7558bf6bbfa6d71f114612f27aa8457eec210","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-04-18T12:11:15Z","title_canon_sha256":"11030aac908a521928915d67ae2c6bf47b1d734ec446ddaec68b6109394ca252"},"schema_version":"1.0","source":{"id":"2204.08271","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2204.08271","created_at":"2026-07-05T04:15:24Z"},{"alias_kind":"arxiv_version","alias_value":"2204.08271v1","created_at":"2026-07-05T04:15:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.08271","created_at":"2026-07-05T04:15:24Z"},{"alias_kind":"pith_short_12","alias_value":"LEEXS4OHWDGT","created_at":"2026-07-05T04:15:24Z"},{"alias_kind":"pith_short_16","alias_value":"LEEXS4OHWDGTOOXO","created_at":"2026-07-05T04:15:24Z"},{"alias_kind":"pith_short_8","alias_value":"LEEXS4OH","created_at":"2026-07-05T04:15:24Z"}],"graph_snapshots":[{"event_id":"sha256:9b9dc7b368f11aa0d66a7490e4ea98550f66e33b8d6f2bdb3b009e84b1fab32c","target":"graph","created_at":"2026-07-05T04:15:24Z","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/2204.08271/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Herbage mass yield and composition estimation is an important tool for dairy farmers to ensure an adequate supply of high quality herbage for grazing and subsequently milk production. By accurately estimating herbage mass and composition, targeted nitrogen fertiliser application strategies can be deployed to improve localised regions in a herbage field, effectively reducing the negative impacts of over-fertilization on biodiversity and the environment. In this context, deep learning algorithms offer a tempting alternative to the usual means of sward composition estimation, which involves the d","authors_text":"Badri Narayanan, Brian Mac Namee, Deirdre Hennessey, Jaime Fernandez, Kevin McGuinness, Mohamed Saadeldin, Noel E. O'Connor, Paul Albert","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-04-18T12:11:15Z","title":"Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.08271","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":"sha256:3e96be02a2703e7a6f41a2bc825b69754b2ba1abcc53268ed08498303c051d8e","target":"record","created_at":"2026-07-05T04:15:24Z","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":"97589f3b1b9438d8fd095af761c7558bf6bbfa6d71f114612f27aa8457eec210","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-04-18T12:11:15Z","title_canon_sha256":"11030aac908a521928915d67ae2c6bf47b1d734ec446ddaec68b6109394ca252"},"schema_version":"1.0","source":{"id":"2204.08271","kind":"arxiv","version":1}},"canonical_sha256":"59097971c7b0cd373aeeca246738e8cc8b376ad1cca343dd506738c66ab4b84e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"59097971c7b0cd373aeeca246738e8cc8b376ad1cca343dd506738c66ab4b84e","first_computed_at":"2026-07-05T04:15:24.159699Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:15:24.159699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zYcp6RTlbJXgWALEOidSAfI3d1rPuuxz8KGgd8MZwNnTAAv5g0/3AZzFD0D6VNNPFpIPk2bCnhiSG5vDHDJ3BA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:15:24.160172Z","signed_message":"canonical_sha256_bytes"},"source_id":"2204.08271","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3e96be02a2703e7a6f41a2bc825b69754b2ba1abcc53268ed08498303c051d8e","sha256:9b9dc7b368f11aa0d66a7490e4ea98550f66e33b8d6f2bdb3b009e84b1fab32c"],"state_sha256":"cfbf59f6651ac4d6437fb864226add74f5b019dbe10cc1a11b86c7bcbc5871e9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BY/fzjfMtRRbcmgqeFWCQMGFwMMTAJcw2hl/8iVq3Yt6q6uIYDMwxrxlMaafLhYRXTGnYcMM5AoYr6iw4BoTDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T23:19:19.669266Z","bundle_sha256":"d4dbf56e412e280222f0769f909e0d30b465f00dbd738db904fc0b552dddd7af"}}