{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:GE7IXKO7LA6ZT4DENZFHPWCB5Z","short_pith_number":"pith:GE7IXKO7","canonical_record":{"source":{"id":"2006.11692","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-06-21T02:26:48Z","cross_cats_sorted":[],"title_canon_sha256":"4d78873f8f403b2c6381e8d49fe7274f36beea771fbc027c16df4dd2b4b7d9d4","abstract_canon_sha256":"ff6eabd52de63d249fd76bafb9bb045003edf6cc436baea14e3c7d488a76383f"},"schema_version":"1.0"},"canonical_sha256":"313e8ba9df583d99f0646e4a77d841ee7c74c9fdc6d373eccc46cee64f54afdd","source":{"kind":"arxiv","id":"2006.11692","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.11692","created_at":"2026-07-05T01:11:52Z"},{"alias_kind":"arxiv_version","alias_value":"2006.11692v1","created_at":"2026-07-05T01:11:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.11692","created_at":"2026-07-05T01:11:52Z"},{"alias_kind":"pith_short_12","alias_value":"GE7IXKO7LA6Z","created_at":"2026-07-05T01:11:52Z"},{"alias_kind":"pith_short_16","alias_value":"GE7IXKO7LA6ZT4DE","created_at":"2026-07-05T01:11:52Z"},{"alias_kind":"pith_short_8","alias_value":"GE7IXKO7","created_at":"2026-07-05T01:11:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:GE7IXKO7LA6ZT4DENZFHPWCB5Z","target":"record","payload":{"canonical_record":{"source":{"id":"2006.11692","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-06-21T02:26:48Z","cross_cats_sorted":[],"title_canon_sha256":"4d78873f8f403b2c6381e8d49fe7274f36beea771fbc027c16df4dd2b4b7d9d4","abstract_canon_sha256":"ff6eabd52de63d249fd76bafb9bb045003edf6cc436baea14e3c7d488a76383f"},"schema_version":"1.0"},"canonical_sha256":"313e8ba9df583d99f0646e4a77d841ee7c74c9fdc6d373eccc46cee64f54afdd","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:11:52.786588Z","signature_b64":"uR5eT4v/FGI4qSqXA9yGDvKY5RVEd89R8mCep4ONL48iUhXlFkjaep9muD7ScUm4Vudya+rIvuzCNI40h65XDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"313e8ba9df583d99f0646e4a77d841ee7c74c9fdc6d373eccc46cee64f54afdd","last_reissued_at":"2026-07-05T01:11:52.786047Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:11:52.786047Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2006.11692","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":"2026-07-05T01:11:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vpY+NlczGa8uoio/ouQDEaQhBtSn/6Ea5y9gNPVsmNPlgxEssyBAiFPV0SRMJvHX5OoOxjXIicPbk+5csdIACw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T17:23:19.797177Z"},"content_sha256":"b902924811d732e7349a7f56f974aa8d728d2542c06558641aa4321a897e2eb9","schema_version":"1.0","event_id":"sha256:b902924811d732e7349a7f56f974aa8d728d2542c06558641aa4321a897e2eb9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:GE7IXKO7LA6ZT4DENZFHPWCB5Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Semi-Supervised Object Detection with Sparsely Annotated Dataset","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jihun Yoon, Min-Kook Choi, Sanha Jeong, SeungBum Hong","submitted_at":"2020-06-21T02:26:48Z","abstract_excerpt":"In training object detector based on convolutional neural networks, selection of effective positive examples for training is an important factor. However, when training an anchor-based detectors with sparse annotations on an image, effort to find effective positive examples can hinder training performance. When using the anchor-based training for the ground truth bounding box to collect positive examples under given IoU, it is often possible to include objects from other classes in the current training class, or objects that are needed to be trained can only be sampled as negative examples. We"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.11692","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/2006.11692/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":"2026-07-05T01:11:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lZM2Qwa4AJrxAOOL+4GCO8IgL96Db4bGnWXkxBbLBiawA+vOPLQqZwOeg4J5fF80exLF+lHe+Z+WmsQ2lqXEDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T17:23:19.797559Z"},"content_sha256":"5cea9ca817865a4062a2f571d154d4221d1b679aede45299cf86bf2507489cf7","schema_version":"1.0","event_id":"sha256:5cea9ca817865a4062a2f571d154d4221d1b679aede45299cf86bf2507489cf7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GE7IXKO7LA6ZT4DENZFHPWCB5Z/bundle.json","state_url":"https://pith.science/pith/GE7IXKO7LA6ZT4DENZFHPWCB5Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GE7IXKO7LA6ZT4DENZFHPWCB5Z/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":"2026-07-13T17:23:19Z","links":{"resolver":"https://pith.science/pith/GE7IXKO7LA6ZT4DENZFHPWCB5Z","bundle":"https://pith.science/pith/GE7IXKO7LA6ZT4DENZFHPWCB5Z/bundle.json","state":"https://pith.science/pith/GE7IXKO7LA6ZT4DENZFHPWCB5Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GE7IXKO7LA6ZT4DENZFHPWCB5Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:GE7IXKO7LA6ZT4DENZFHPWCB5Z","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":"ff6eabd52de63d249fd76bafb9bb045003edf6cc436baea14e3c7d488a76383f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-06-21T02:26:48Z","title_canon_sha256":"4d78873f8f403b2c6381e8d49fe7274f36beea771fbc027c16df4dd2b4b7d9d4"},"schema_version":"1.0","source":{"id":"2006.11692","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.11692","created_at":"2026-07-05T01:11:52Z"},{"alias_kind":"arxiv_version","alias_value":"2006.11692v1","created_at":"2026-07-05T01:11:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.11692","created_at":"2026-07-05T01:11:52Z"},{"alias_kind":"pith_short_12","alias_value":"GE7IXKO7LA6Z","created_at":"2026-07-05T01:11:52Z"},{"alias_kind":"pith_short_16","alias_value":"GE7IXKO7LA6ZT4DE","created_at":"2026-07-05T01:11:52Z"},{"alias_kind":"pith_short_8","alias_value":"GE7IXKO7","created_at":"2026-07-05T01:11:52Z"}],"graph_snapshots":[{"event_id":"sha256:5cea9ca817865a4062a2f571d154d4221d1b679aede45299cf86bf2507489cf7","target":"graph","created_at":"2026-07-05T01:11:52Z","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/2006.11692/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In training object detector based on convolutional neural networks, selection of effective positive examples for training is an important factor. However, when training an anchor-based detectors with sparse annotations on an image, effort to find effective positive examples can hinder training performance. When using the anchor-based training for the ground truth bounding box to collect positive examples under given IoU, it is often possible to include objects from other classes in the current training class, or objects that are needed to be trained can only be sampled as negative examples. We","authors_text":"Jihun Yoon, Min-Kook Choi, Sanha Jeong, SeungBum Hong","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-06-21T02:26:48Z","title":"Semi-Supervised Object Detection with Sparsely Annotated Dataset"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.11692","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:b902924811d732e7349a7f56f974aa8d728d2542c06558641aa4321a897e2eb9","target":"record","created_at":"2026-07-05T01:11:52Z","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":"ff6eabd52de63d249fd76bafb9bb045003edf6cc436baea14e3c7d488a76383f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2020-06-21T02:26:48Z","title_canon_sha256":"4d78873f8f403b2c6381e8d49fe7274f36beea771fbc027c16df4dd2b4b7d9d4"},"schema_version":"1.0","source":{"id":"2006.11692","kind":"arxiv","version":1}},"canonical_sha256":"313e8ba9df583d99f0646e4a77d841ee7c74c9fdc6d373eccc46cee64f54afdd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"313e8ba9df583d99f0646e4a77d841ee7c74c9fdc6d373eccc46cee64f54afdd","first_computed_at":"2026-07-05T01:11:52.786047Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:11:52.786047Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uR5eT4v/FGI4qSqXA9yGDvKY5RVEd89R8mCep4ONL48iUhXlFkjaep9muD7ScUm4Vudya+rIvuzCNI40h65XDw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:11:52.786588Z","signed_message":"canonical_sha256_bytes"},"source_id":"2006.11692","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b902924811d732e7349a7f56f974aa8d728d2542c06558641aa4321a897e2eb9","sha256:5cea9ca817865a4062a2f571d154d4221d1b679aede45299cf86bf2507489cf7"],"state_sha256":"dc51a1c8bb7599cacf2475ecd4edddb1ec5b997b1520de4293076f82b967d5ef"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AVSHJXYBZRHggGVndPUQY235r/oq6v3si/UWDh+/WtNP+ADhk65EyHEHPl0OxeQqPCKHMBu/IZjo3q46q4e7Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-13T17:23:19.799785Z","bundle_sha256":"ed8149b1490542ab20d6485d3c34fdba09f6c98d1d6d9c8fc05c0452753ff47a"}}