{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:35C7SXTO5ZHTCNONJSNL4KYNS6","short_pith_number":"pith:35C7SXTO","canonical_record":{"source":{"id":"1908.08244","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-22T08:10:23Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"84a4d387816b3dee5c74b141987ba966aac5b346eb8ccb4cc998c9580d9fb639","abstract_canon_sha256":"22ec395ba109818e770fc8357f64e9206e253193b91bb51a3393689476bb0916"},"schema_version":"1.0"},"canonical_sha256":"df45f95e6eee4f3135cd4c9abe2b0d97a9c671058dec2b51bc58af4016832716","source":{"kind":"arxiv","id":"1908.08244","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.08244","created_at":"2026-07-04T23:59:11Z"},{"alias_kind":"arxiv_version","alias_value":"1908.08244v1","created_at":"2026-07-04T23:59:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.08244","created_at":"2026-07-04T23:59:11Z"},{"alias_kind":"pith_short_12","alias_value":"35C7SXTO5ZHT","created_at":"2026-07-04T23:59:11Z"},{"alias_kind":"pith_short_16","alias_value":"35C7SXTO5ZHTCNON","created_at":"2026-07-04T23:59:11Z"},{"alias_kind":"pith_short_8","alias_value":"35C7SXTO","created_at":"2026-07-04T23:59:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:35C7SXTO5ZHTCNONJSNL4KYNS6","target":"record","payload":{"canonical_record":{"source":{"id":"1908.08244","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-22T08:10:23Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"84a4d387816b3dee5c74b141987ba966aac5b346eb8ccb4cc998c9580d9fb639","abstract_canon_sha256":"22ec395ba109818e770fc8357f64e9206e253193b91bb51a3393689476bb0916"},"schema_version":"1.0"},"canonical_sha256":"df45f95e6eee4f3135cd4c9abe2b0d97a9c671058dec2b51bc58af4016832716","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:59:11.031452Z","signature_b64":"nMlT+P4DgK9Tc92+6x1w0vCm5riAe6TMzMSPiCgN2QVY+Hc+vfIPrxQt9N0+z4e+Ujfi3U9ZLHq/+gxlZUulCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"df45f95e6eee4f3135cd4c9abe2b0d97a9c671058dec2b51bc58af4016832716","last_reissued_at":"2026-07-04T23:59:11.031007Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:59:11.031007Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.08244","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":"2026-07-04T23:59:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jKf/UcrzqCRxo6EaVt58FT/pbtGBBS/il/awMlJCQeKvK7MLA+RAvZXl8+IqGB/lWiG4QG0YZO5tLlqe7or4Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T05:01:50.429295Z"},"content_sha256":"2309f11c6af781c8636e774b902d7da6bfc3bea50a2c59d803da355a30de4ce2","schema_version":"1.0","event_id":"sha256:2309f11c6af781c8636e774b902d7da6bfc3bea50a2c59d803da355a30de4ce2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:35C7SXTO5ZHTCNONJSNL4KYNS6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Object detection on aerial imagery using CenterNet","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Dheeraj Reddy Pailla, Sai Saketh Chennamsetty, Varghese Kollerathu","submitted_at":"2019-08-22T08:10:23Z","abstract_excerpt":"Detection and classification of objects in aerial imagery have several applications like urban planning, crop surveillance, and traffic surveillance. However, due to the lower resolution of the objects and the effect of noise in aerial images, extracting distinguishing features for the objects is a challenge. We evaluate CenterNet, a state of the art method for real-time 2D object detection, on the VisDrone2019 dataset. We evaluate the performance of the model with different backbone networks in conjunction with varying resolutions during training and testing."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.08244","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/1908.08244/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":"2026-07-04T23:59:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G5JXowre0xKabDMWSc+6La6Pz0ydCe+Z6rcKfKuETSxZ/92bh/kxpCajOxPhh2347eWvdZ8xzrqPDg5Xv4mODw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T05:01:50.430048Z"},"content_sha256":"853d91fd540a0ce7fed3d76e9b3c760be840bd424c7018c21b47df83ffaf473e","schema_version":"1.0","event_id":"sha256:853d91fd540a0ce7fed3d76e9b3c760be840bd424c7018c21b47df83ffaf473e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/35C7SXTO5ZHTCNONJSNL4KYNS6/bundle.json","state_url":"https://pith.science/pith/35C7SXTO5ZHTCNONJSNL4KYNS6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/35C7SXTO5ZHTCNONJSNL4KYNS6/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":"2026-08-16T05:01:50Z","links":{"resolver":"https://pith.science/pith/35C7SXTO5ZHTCNONJSNL4KYNS6","bundle":"https://pith.science/pith/35C7SXTO5ZHTCNONJSNL4KYNS6/bundle.json","state":"https://pith.science/pith/35C7SXTO5ZHTCNONJSNL4KYNS6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/35C7SXTO5ZHTCNONJSNL4KYNS6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:35C7SXTO5ZHTCNONJSNL4KYNS6","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":"22ec395ba109818e770fc8357f64e9206e253193b91bb51a3393689476bb0916","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-22T08:10:23Z","title_canon_sha256":"84a4d387816b3dee5c74b141987ba966aac5b346eb8ccb4cc998c9580d9fb639"},"schema_version":"1.0","source":{"id":"1908.08244","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.08244","created_at":"2026-07-04T23:59:11Z"},{"alias_kind":"arxiv_version","alias_value":"1908.08244v1","created_at":"2026-07-04T23:59:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.08244","created_at":"2026-07-04T23:59:11Z"},{"alias_kind":"pith_short_12","alias_value":"35C7SXTO5ZHT","created_at":"2026-07-04T23:59:11Z"},{"alias_kind":"pith_short_16","alias_value":"35C7SXTO5ZHTCNON","created_at":"2026-07-04T23:59:11Z"},{"alias_kind":"pith_short_8","alias_value":"35C7SXTO","created_at":"2026-07-04T23:59:11Z"}],"graph_snapshots":[{"event_id":"sha256:853d91fd540a0ce7fed3d76e9b3c760be840bd424c7018c21b47df83ffaf473e","target":"graph","created_at":"2026-07-04T23:59:11Z","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/1908.08244/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Detection and classification of objects in aerial imagery have several applications like urban planning, crop surveillance, and traffic surveillance. However, due to the lower resolution of the objects and the effect of noise in aerial images, extracting distinguishing features for the objects is a challenge. We evaluate CenterNet, a state of the art method for real-time 2D object detection, on the VisDrone2019 dataset. We evaluate the performance of the model with different backbone networks in conjunction with varying resolutions during training and testing.","authors_text":"Dheeraj Reddy Pailla, Sai Saketh Chennamsetty, Varghese Kollerathu","cross_cats":["cs.RO"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-22T08:10:23Z","title":"Object detection on aerial imagery using CenterNet"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.08244","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":"sha256:2309f11c6af781c8636e774b902d7da6bfc3bea50a2c59d803da355a30de4ce2","target":"record","created_at":"2026-07-04T23:59:11Z","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":"22ec395ba109818e770fc8357f64e9206e253193b91bb51a3393689476bb0916","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CV","submitted_at":"2019-08-22T08:10:23Z","title_canon_sha256":"84a4d387816b3dee5c74b141987ba966aac5b346eb8ccb4cc998c9580d9fb639"},"schema_version":"1.0","source":{"id":"1908.08244","kind":"arxiv","version":1}},"canonical_sha256":"df45f95e6eee4f3135cd4c9abe2b0d97a9c671058dec2b51bc58af4016832716","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"df45f95e6eee4f3135cd4c9abe2b0d97a9c671058dec2b51bc58af4016832716","first_computed_at":"2026-07-04T23:59:11.031007Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:59:11.031007Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nMlT+P4DgK9Tc92+6x1w0vCm5riAe6TMzMSPiCgN2QVY+Hc+vfIPrxQt9N0+z4e+Ujfi3U9ZLHq/+gxlZUulCQ==","signature_status":"signed_v1","signed_at":"2026-07-04T23:59:11.031452Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.08244","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2309f11c6af781c8636e774b902d7da6bfc3bea50a2c59d803da355a30de4ce2","sha256:853d91fd540a0ce7fed3d76e9b3c760be840bd424c7018c21b47df83ffaf473e"],"state_sha256":"268301a4ab830c4775671ae053f6c3b9270ba68030402eca8d104bf619c7c002"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UYm+2pmVtL/zSwMie3ly0A46IYrf66+OUfPffZFdmJrNQlJZjnIPCPipHV9kBUvyEndWdGKVbrER+WrVJf2JBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T05:01:50.435404Z","bundle_sha256":"85a4b8e8621e09e671dc0e6ebf1a08e7c2c888edf59b09574d1772b9c263f2ec"}}