{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:WWHLMKYIXVVLZAB72YVMNH5URA","short_pith_number":"pith:WWHLMKYI","canonical_record":{"source":{"id":"1812.01157","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-04T01:18:05Z","cross_cats_sorted":[],"title_canon_sha256":"6e12780699b9710a5c89dc8c8353f332a7ef03f5270823453f02e9c11112d31a","abstract_canon_sha256":"a4fe88b8fca6b4b254eca2f9a90635e163071f6a7465360b7e7a96b9f6845fdf"},"schema_version":"1.0"},"canonical_sha256":"b58eb62b08bd6abc803fd62ac69fb4882d8820424773a74ea110424b651b32f3","source":{"kind":"arxiv","id":"1812.01157","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.01157","created_at":"2026-05-17T23:43:17Z"},{"alias_kind":"arxiv_version","alias_value":"1812.01157v2","created_at":"2026-05-17T23:43:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.01157","created_at":"2026-05-17T23:43:17Z"},{"alias_kind":"pith_short_12","alias_value":"WWHLMKYIXVVL","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WWHLMKYIXVVLZAB7","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WWHLMKYI","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:WWHLMKYIXVVLZAB72YVMNH5URA","target":"record","payload":{"canonical_record":{"source":{"id":"1812.01157","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-04T01:18:05Z","cross_cats_sorted":[],"title_canon_sha256":"6e12780699b9710a5c89dc8c8353f332a7ef03f5270823453f02e9c11112d31a","abstract_canon_sha256":"a4fe88b8fca6b4b254eca2f9a90635e163071f6a7465360b7e7a96b9f6845fdf"},"schema_version":"1.0"},"canonical_sha256":"b58eb62b08bd6abc803fd62ac69fb4882d8820424773a74ea110424b651b32f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:43:17.082425Z","signature_b64":"7BrgEjOoIvCii25/Q7RmJhhETCZZuBPEsowwO6wc0PLeLWj8Psnmsogz+JZ6oHRzIhD+ICrEzR8gf+rNqbZ7CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b58eb62b08bd6abc803fd62ac69fb4882d8820424773a74ea110424b651b32f3","last_reissued_at":"2026-05-17T23:43:17.081849Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:43:17.081849Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.01157","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":"2026-05-17T23:43:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LKV2XdPk6C+cHRnkfJDSuKRToOpE0EzYya9wH+IhcFdB0ad9eK/t6sHbMMkBBFurrsOfrueNTCwtVW4ZEGXbAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T13:22:56.843599Z"},"content_sha256":"ee359bf4b7b07c83fa089b0a68705c0b16a51d3524749af90c8cda1fc79de376","schema_version":"1.0","event_id":"sha256:ee359bf4b7b07c83fa089b0a68705c0b16a51d3524749af90c8cda1fc79de376"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:WWHLMKYIXVVLZAB72YVMNH5URA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alexander Matveev, David Rolnick, Hayk Saribekyan, Lu Mi, Nir Shavit, Yaron Meirovitch","submitted_at":"2018-12-04T01:18:05Z","abstract_excerpt":"Pixel-accurate tracking of objects is a key element in many computer vision applications, often solved by iterated individual object tracking or instance segmentation followed by object matching. Here we introduce cross-classification clustering (3C), a technique that simultaneously tracks complex, interrelated objects in an image stack. The key idea in cross-classification is to efficiently turn a clustering problem into a classification problem by running a logarithmic number of independent classifications per image, letting the cross-labeling of these classifications uniquely classify each "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.01157","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":"2026-05-17T23:43:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tRux3CU+M+ua3GqKBoJq0kr1yg0wUgQjvzw/pI676VZncCGbcx60V0kSkwAX2u0+d2e2adls+FwRNvClYj8AAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T13:22:56.844001Z"},"content_sha256":"8e931299d4d6d49106abc05ab3c93d513de65227f7e6b24eca2556dad50a0adb","schema_version":"1.0","event_id":"sha256:8e931299d4d6d49106abc05ab3c93d513de65227f7e6b24eca2556dad50a0adb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WWHLMKYIXVVLZAB72YVMNH5URA/bundle.json","state_url":"https://pith.science/pith/WWHLMKYIXVVLZAB72YVMNH5URA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WWHLMKYIXVVLZAB72YVMNH5URA/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":"2026-06-01T13:22:56Z","links":{"resolver":"https://pith.science/pith/WWHLMKYIXVVLZAB72YVMNH5URA","bundle":"https://pith.science/pith/WWHLMKYIXVVLZAB72YVMNH5URA/bundle.json","state":"https://pith.science/pith/WWHLMKYIXVVLZAB72YVMNH5URA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WWHLMKYIXVVLZAB72YVMNH5URA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:WWHLMKYIXVVLZAB72YVMNH5URA","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":"a4fe88b8fca6b4b254eca2f9a90635e163071f6a7465360b7e7a96b9f6845fdf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-04T01:18:05Z","title_canon_sha256":"6e12780699b9710a5c89dc8c8353f332a7ef03f5270823453f02e9c11112d31a"},"schema_version":"1.0","source":{"id":"1812.01157","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.01157","created_at":"2026-05-17T23:43:17Z"},{"alias_kind":"arxiv_version","alias_value":"1812.01157v2","created_at":"2026-05-17T23:43:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.01157","created_at":"2026-05-17T23:43:17Z"},{"alias_kind":"pith_short_12","alias_value":"WWHLMKYIXVVL","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WWHLMKYIXVVLZAB7","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WWHLMKYI","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:8e931299d4d6d49106abc05ab3c93d513de65227f7e6b24eca2556dad50a0adb","target":"graph","created_at":"2026-05-17T23:43:17Z","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":"Pixel-accurate tracking of objects is a key element in many computer vision applications, often solved by iterated individual object tracking or instance segmentation followed by object matching. Here we introduce cross-classification clustering (3C), a technique that simultaneously tracks complex, interrelated objects in an image stack. The key idea in cross-classification is to efficiently turn a clustering problem into a classification problem by running a logarithmic number of independent classifications per image, letting the cross-labeling of these classifications uniquely classify each ","authors_text":"Alexander Matveev, David Rolnick, Hayk Saribekyan, Lu Mi, Nir Shavit, Yaron Meirovitch","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-04T01:18:05Z","title":"Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.01157","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:ee359bf4b7b07c83fa089b0a68705c0b16a51d3524749af90c8cda1fc79de376","target":"record","created_at":"2026-05-17T23:43:17Z","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":"a4fe88b8fca6b4b254eca2f9a90635e163071f6a7465360b7e7a96b9f6845fdf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-04T01:18:05Z","title_canon_sha256":"6e12780699b9710a5c89dc8c8353f332a7ef03f5270823453f02e9c11112d31a"},"schema_version":"1.0","source":{"id":"1812.01157","kind":"arxiv","version":2}},"canonical_sha256":"b58eb62b08bd6abc803fd62ac69fb4882d8820424773a74ea110424b651b32f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b58eb62b08bd6abc803fd62ac69fb4882d8820424773a74ea110424b651b32f3","first_computed_at":"2026-05-17T23:43:17.081849Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:43:17.081849Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7BrgEjOoIvCii25/Q7RmJhhETCZZuBPEsowwO6wc0PLeLWj8Psnmsogz+JZ6oHRzIhD+ICrEzR8gf+rNqbZ7CQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:43:17.082425Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.01157","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ee359bf4b7b07c83fa089b0a68705c0b16a51d3524749af90c8cda1fc79de376","sha256:8e931299d4d6d49106abc05ab3c93d513de65227f7e6b24eca2556dad50a0adb"],"state_sha256":"477320d1bf1d7bbecfbf3372b55ab3e32adeb91de054a25468c9a78fb161a647"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WTHnEh6uWxOAfBLniTVcG4MEWZ26+2WH0TuIKHPlveeVaYZ8iUvmkF6BwFtjqq3LCnNuA1mBwGG2mJZkXgaTCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T13:22:56.846526Z","bundle_sha256":"03b21bf792a8f97afc525d2a8adb3441c5a509702ffb1193e8dab610f9576f6e"}}