{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:VIAQEODLCCTB7ZV2G7ESNPF6QC","short_pith_number":"pith:VIAQEODL","canonical_record":{"source":{"id":"2208.07722","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-16T12:35:57Z","cross_cats_sorted":[],"title_canon_sha256":"4cfe7e5312e5603c2a9998aa3d82d3adda14496bd82f6e5371f1a323b8286761","abstract_canon_sha256":"bd16548c7f06c6a3e183ef2ddd9a78ee48d34cb9292a387db9738fe2d81cdaeb"},"schema_version":"1.0"},"canonical_sha256":"aa0102386b10a61fe6ba37c926bcbe809300f4992f73d0d24336a2317acedee8","source":{"kind":"arxiv","id":"2208.07722","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.07722","created_at":"2026-07-05T05:41:25Z"},{"alias_kind":"arxiv_version","alias_value":"2208.07722v2","created_at":"2026-07-05T05:41:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.07722","created_at":"2026-07-05T05:41:25Z"},{"alias_kind":"pith_short_12","alias_value":"VIAQEODLCCTB","created_at":"2026-07-05T05:41:25Z"},{"alias_kind":"pith_short_16","alias_value":"VIAQEODLCCTB7ZV2","created_at":"2026-07-05T05:41:25Z"},{"alias_kind":"pith_short_8","alias_value":"VIAQEODL","created_at":"2026-07-05T05:41:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:VIAQEODLCCTB7ZV2G7ESNPF6QC","target":"record","payload":{"canonical_record":{"source":{"id":"2208.07722","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-16T12:35:57Z","cross_cats_sorted":[],"title_canon_sha256":"4cfe7e5312e5603c2a9998aa3d82d3adda14496bd82f6e5371f1a323b8286761","abstract_canon_sha256":"bd16548c7f06c6a3e183ef2ddd9a78ee48d34cb9292a387db9738fe2d81cdaeb"},"schema_version":"1.0"},"canonical_sha256":"aa0102386b10a61fe6ba37c926bcbe809300f4992f73d0d24336a2317acedee8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:41:25.137082Z","signature_b64":"3PzPZnFu/WJWt4tOQT+wpYVceshxkxSG+ngdKVdYEOzmd3Pb7cXUfpP5jthGtVOPn7XIVFeodTWa/j6ilwIUDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aa0102386b10a61fe6ba37c926bcbe809300f4992f73d0d24336a2317acedee8","last_reissued_at":"2026-07-05T05:41:25.136549Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:41:25.136549Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2208.07722","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":"2026-07-05T05:41:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8vql4OjWTGkVK8uUdzxOiC94QjmPurobCe2284T4n83WBc7PGG3t0VVv8pVzJydaEO7ZhhaH3ZTmrjXVHhBhCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T05:17:15.325285Z"},"content_sha256":"e4f9e7097d313b6fc9ed221a2432dbb246f68716b4f158455a01d640073ee73a","schema_version":"1.0","event_id":"sha256:e4f9e7097d313b6fc9ed221a2432dbb246f68716b4f158455a01d640073ee73a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:VIAQEODLCCTB7ZV2G7ESNPF6QC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unsupervised domain adaptation semantic segmentation of high-resolution remote sensing imagery with invariant domain-level prototype memory","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Geng Sun, Jie Chen, Jingru Zhu, Libo Yang, Min Deng, Ya Guo","submitted_at":"2022-08-16T12:35:57Z","abstract_excerpt":"Semantic segmentation is a key technique involved in automatic interpretation of high-resolution remote sensing (HRS) imagery and has drawn much attention in the remote sensing community. Deep convolutional neural networks (DCNNs) have been successfully applied to the HRS imagery semantic segmentation task due to their hierarchical representation ability. However, the heavy dependency on a large number of training data with dense annotation and the sensitiveness to the variation of data distribution severely restrict the potential application of DCNNs for the semantic segmentation of HRS image"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.07722","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2208.07722/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":"2026-07-05T05:41:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"66tH7rx8/XdvxMxY4bQuKQAYcWaAkiAUdXh49+6JxukuwXthET1eJo0KCLndMG2w6m8OLljfDiv30xL9fh00AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T05:17:15.325997Z"},"content_sha256":"890d4a738d78972ab872e6eb79b3fab46da2322313adee1838c8b164fea67a13","schema_version":"1.0","event_id":"sha256:890d4a738d78972ab872e6eb79b3fab46da2322313adee1838c8b164fea67a13"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VIAQEODLCCTB7ZV2G7ESNPF6QC/bundle.json","state_url":"https://pith.science/pith/VIAQEODLCCTB7ZV2G7ESNPF6QC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VIAQEODLCCTB7ZV2G7ESNPF6QC/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":"2026-07-07T05:17:15Z","links":{"resolver":"https://pith.science/pith/VIAQEODLCCTB7ZV2G7ESNPF6QC","bundle":"https://pith.science/pith/VIAQEODLCCTB7ZV2G7ESNPF6QC/bundle.json","state":"https://pith.science/pith/VIAQEODLCCTB7ZV2G7ESNPF6QC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VIAQEODLCCTB7ZV2G7ESNPF6QC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:VIAQEODLCCTB7ZV2G7ESNPF6QC","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":"bd16548c7f06c6a3e183ef2ddd9a78ee48d34cb9292a387db9738fe2d81cdaeb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-16T12:35:57Z","title_canon_sha256":"4cfe7e5312e5603c2a9998aa3d82d3adda14496bd82f6e5371f1a323b8286761"},"schema_version":"1.0","source":{"id":"2208.07722","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.07722","created_at":"2026-07-05T05:41:25Z"},{"alias_kind":"arxiv_version","alias_value":"2208.07722v2","created_at":"2026-07-05T05:41:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.07722","created_at":"2026-07-05T05:41:25Z"},{"alias_kind":"pith_short_12","alias_value":"VIAQEODLCCTB","created_at":"2026-07-05T05:41:25Z"},{"alias_kind":"pith_short_16","alias_value":"VIAQEODLCCTB7ZV2","created_at":"2026-07-05T05:41:25Z"},{"alias_kind":"pith_short_8","alias_value":"VIAQEODL","created_at":"2026-07-05T05:41:25Z"}],"graph_snapshots":[{"event_id":"sha256:890d4a738d78972ab872e6eb79b3fab46da2322313adee1838c8b164fea67a13","target":"graph","created_at":"2026-07-05T05:41:25Z","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/2208.07722/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semantic segmentation is a key technique involved in automatic interpretation of high-resolution remote sensing (HRS) imagery and has drawn much attention in the remote sensing community. Deep convolutional neural networks (DCNNs) have been successfully applied to the HRS imagery semantic segmentation task due to their hierarchical representation ability. However, the heavy dependency on a large number of training data with dense annotation and the sensitiveness to the variation of data distribution severely restrict the potential application of DCNNs for the semantic segmentation of HRS image","authors_text":"Geng Sun, Jie Chen, Jingru Zhu, Libo Yang, Min Deng, Ya Guo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-16T12:35:57Z","title":"Unsupervised domain adaptation semantic segmentation of high-resolution remote sensing imagery with invariant domain-level prototype memory"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.07722","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:e4f9e7097d313b6fc9ed221a2432dbb246f68716b4f158455a01d640073ee73a","target":"record","created_at":"2026-07-05T05:41:25Z","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":"bd16548c7f06c6a3e183ef2ddd9a78ee48d34cb9292a387db9738fe2d81cdaeb","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-16T12:35:57Z","title_canon_sha256":"4cfe7e5312e5603c2a9998aa3d82d3adda14496bd82f6e5371f1a323b8286761"},"schema_version":"1.0","source":{"id":"2208.07722","kind":"arxiv","version":2}},"canonical_sha256":"aa0102386b10a61fe6ba37c926bcbe809300f4992f73d0d24336a2317acedee8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aa0102386b10a61fe6ba37c926bcbe809300f4992f73d0d24336a2317acedee8","first_computed_at":"2026-07-05T05:41:25.136549Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:41:25.136549Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3PzPZnFu/WJWt4tOQT+wpYVceshxkxSG+ngdKVdYEOzmd3Pb7cXUfpP5jthGtVOPn7XIVFeodTWa/j6ilwIUDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:41:25.137082Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.07722","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4f9e7097d313b6fc9ed221a2432dbb246f68716b4f158455a01d640073ee73a","sha256:890d4a738d78972ab872e6eb79b3fab46da2322313adee1838c8b164fea67a13"],"state_sha256":"ccc640a25f8bf87ee3de40418d2c1e3ae46e6d29c7ea06c8a4888b46c29cd860"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eqzA0KHmPaaM+c8GwU1vwYAzEHFhkjnvh6OkwsrE4nNrVyQ5Pj/cTF7M4Pqp4ohHBMWuq6jKyFR4qLFMvqYvBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T05:17:15.329623Z","bundle_sha256":"c97ab47a5ad446a1e797045be98a305c2936ac5c7cbe62d49a8abc36a78afc5d"}}