{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:HIXHRYKQ4NVOQDPDE7MLIY3QI2","short_pith_number":"pith:HIXHRYKQ","canonical_record":{"source":{"id":"1710.00241","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-30T18:31:53Z","cross_cats_sorted":[],"title_canon_sha256":"edbc0d3c266e8ba8ee0e397bf02c46b45ba08ca8ed5d7477737165b507ad62dc","abstract_canon_sha256":"7249f99aaf953e42f335548b71c650590de26436dda7623a3a9242eb0301412e"},"schema_version":"1.0"},"canonical_sha256":"3a2e78e150e36ae80de327d8b463704697449ce55a062af20d073e680a837bfc","source":{"kind":"arxiv","id":"1710.00241","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.00241","created_at":"2026-05-18T00:24:59Z"},{"alias_kind":"arxiv_version","alias_value":"1710.00241v2","created_at":"2026-05-18T00:24:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.00241","created_at":"2026-05-18T00:24:59Z"},{"alias_kind":"pith_short_12","alias_value":"HIXHRYKQ4NVO","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HIXHRYKQ4NVOQDPD","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HIXHRYKQ","created_at":"2026-05-18T12:31:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:HIXHRYKQ4NVOQDPDE7MLIY3QI2","target":"record","payload":{"canonical_record":{"source":{"id":"1710.00241","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-30T18:31:53Z","cross_cats_sorted":[],"title_canon_sha256":"edbc0d3c266e8ba8ee0e397bf02c46b45ba08ca8ed5d7477737165b507ad62dc","abstract_canon_sha256":"7249f99aaf953e42f335548b71c650590de26436dda7623a3a9242eb0301412e"},"schema_version":"1.0"},"canonical_sha256":"3a2e78e150e36ae80de327d8b463704697449ce55a062af20d073e680a837bfc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:24:59.580893Z","signature_b64":"z4IbjdkpiU3wzOwEEbLzcu8bQi5hfW1f5JxRiGKnTYxDsy5p95O1iVoQDCMVcmRts+Yit7gAFPL/KKHcNj7pDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3a2e78e150e36ae80de327d8b463704697449ce55a062af20d073e680a837bfc","last_reissued_at":"2026-05-18T00:24:59.580494Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:24:59.580494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1710.00241","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":"2026-05-18T00:24:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Mr016EjbYWVt5l56m1uEf2UYp8XXrR4olQfu60cb8ed3UsLf96fdQzekJO4jVh2CstEXogrK0JMFfsTwJB/bAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T21:29:23.644017Z"},"content_sha256":"027f8960f6af39723697af3cddc443fb5d86151dde7bf23e9f1dff9b1b5f5371","schema_version":"1.0","event_id":"sha256:027f8960f6af39723697af3cddc443fb5d86151dde7bf23e9f1dff9b1b5f5371"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:HIXHRYKQ4NVOQDPDE7MLIY3QI2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anique Josuttes, Curtis Pozniak, Hema Sudhakar Duddu, Ian Stavness, Ilya Ovsyannikov, Imran Ahmed, Keegan Strueby, Shubhra Aich, Steve Shirtliffe","submitted_at":"2017-09-30T18:31:53Z","abstract_excerpt":"In this paper, we investigate estimating emergence and biomass traits from color images and elevation maps of wheat field plots. We employ a state-of-the-art deconvolutional network for segmentation and convolutional architectures, with residual and Inception-like layers, to estimate traits via high dimensional nonlinear regression. Evaluation was performed on two different species of wheat, grown in field plots for an experimental plant breeding study. Our framework achieves satisfactory performance with mean and standard deviation of absolute difference of 1.05 and 1.40 counts for emergence "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.00241","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":""},"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":"2026-05-18T00:24:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"chJVk8Xs568OqryYJ4Svpu713yY+kcqtq/owVgi7fLbTRHZZmTvpmN3QbRzGa7aSUM6wBjTfOnG46k6XdQGNDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T21:29:23.644708Z"},"content_sha256":"58b600160962ef60b2e87a33dbb769e512b5a18c6f6933818a0846a20095cf44","schema_version":"1.0","event_id":"sha256:58b600160962ef60b2e87a33dbb769e512b5a18c6f6933818a0846a20095cf44"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HIXHRYKQ4NVOQDPDE7MLIY3QI2/bundle.json","state_url":"https://pith.science/pith/HIXHRYKQ4NVOQDPDE7MLIY3QI2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HIXHRYKQ4NVOQDPDE7MLIY3QI2/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":"2026-06-11T21:29:23Z","links":{"resolver":"https://pith.science/pith/HIXHRYKQ4NVOQDPDE7MLIY3QI2","bundle":"https://pith.science/pith/HIXHRYKQ4NVOQDPDE7MLIY3QI2/bundle.json","state":"https://pith.science/pith/HIXHRYKQ4NVOQDPDE7MLIY3QI2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HIXHRYKQ4NVOQDPDE7MLIY3QI2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:HIXHRYKQ4NVOQDPDE7MLIY3QI2","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":"7249f99aaf953e42f335548b71c650590de26436dda7623a3a9242eb0301412e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-30T18:31:53Z","title_canon_sha256":"edbc0d3c266e8ba8ee0e397bf02c46b45ba08ca8ed5d7477737165b507ad62dc"},"schema_version":"1.0","source":{"id":"1710.00241","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1710.00241","created_at":"2026-05-18T00:24:59Z"},{"alias_kind":"arxiv_version","alias_value":"1710.00241v2","created_at":"2026-05-18T00:24:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.00241","created_at":"2026-05-18T00:24:59Z"},{"alias_kind":"pith_short_12","alias_value":"HIXHRYKQ4NVO","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HIXHRYKQ4NVOQDPD","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HIXHRYKQ","created_at":"2026-05-18T12:31:18Z"}],"graph_snapshots":[{"event_id":"sha256:58b600160962ef60b2e87a33dbb769e512b5a18c6f6933818a0846a20095cf44","target":"graph","created_at":"2026-05-18T00:24:59Z","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"},"paper":{"abstract_excerpt":"In this paper, we investigate estimating emergence and biomass traits from color images and elevation maps of wheat field plots. We employ a state-of-the-art deconvolutional network for segmentation and convolutional architectures, with residual and Inception-like layers, to estimate traits via high dimensional nonlinear regression. Evaluation was performed on two different species of wheat, grown in field plots for an experimental plant breeding study. Our framework achieves satisfactory performance with mean and standard deviation of absolute difference of 1.05 and 1.40 counts for emergence ","authors_text":"Anique Josuttes, Curtis Pozniak, Hema Sudhakar Duddu, Ian Stavness, Ilya Ovsyannikov, Imran Ahmed, Keegan Strueby, Shubhra Aich, Steve Shirtliffe","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-30T18:31:53Z","title":"DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.00241","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":"sha256:027f8960f6af39723697af3cddc443fb5d86151dde7bf23e9f1dff9b1b5f5371","target":"record","created_at":"2026-05-18T00:24:59Z","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":"7249f99aaf953e42f335548b71c650590de26436dda7623a3a9242eb0301412e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-09-30T18:31:53Z","title_canon_sha256":"edbc0d3c266e8ba8ee0e397bf02c46b45ba08ca8ed5d7477737165b507ad62dc"},"schema_version":"1.0","source":{"id":"1710.00241","kind":"arxiv","version":2}},"canonical_sha256":"3a2e78e150e36ae80de327d8b463704697449ce55a062af20d073e680a837bfc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3a2e78e150e36ae80de327d8b463704697449ce55a062af20d073e680a837bfc","first_computed_at":"2026-05-18T00:24:59.580494Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:24:59.580494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"z4IbjdkpiU3wzOwEEbLzcu8bQi5hfW1f5JxRiGKnTYxDsy5p95O1iVoQDCMVcmRts+Yit7gAFPL/KKHcNj7pDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:24:59.580893Z","signed_message":"canonical_sha256_bytes"},"source_id":"1710.00241","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:027f8960f6af39723697af3cddc443fb5d86151dde7bf23e9f1dff9b1b5f5371","sha256:58b600160962ef60b2e87a33dbb769e512b5a18c6f6933818a0846a20095cf44"],"state_sha256":"2cec85ca8c6983b0e6d2a1228942ca6956098a466ce82a55d7732491ac5406c6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZNeUAaZ4a97ySdf/k5vhk7gcJsgzA453uH6ASO49aHnQZtrNLUq+KXGHyxBjXyjkIt5+VzxLGpJ+nabaw2vpCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T21:29:23.648227Z","bundle_sha256":"f75783ba1bf16fec76c1230e65cdb05c9fe15a69171f0b7dc96844bca962fe47"}}