{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:ALQ4BQAY4COAYOYMQTLQ4YZYZM","short_pith_number":"pith:ALQ4BQAY","canonical_record":{"source":{"id":"2206.01096","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-06-02T15:22:29Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"0b9b29ea0c51b0fb49b1eaceef398ec88bd5cae4b21170f45314a953b70c3c81","abstract_canon_sha256":"e0e9a0f5188939c1a4e2d396d6ee115b529585f22639ed7900529d834735927b"},"schema_version":"1.0"},"canonical_sha256":"02e1c0c018e09c0c3b0c84d70e6338cb24cebcaff76ed238a978dac87874fb7a","source":{"kind":"arxiv","id":"2206.01096","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.01096","created_at":"2026-07-05T04:28:36Z"},{"alias_kind":"arxiv_version","alias_value":"2206.01096v1","created_at":"2026-07-05T04:28:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.01096","created_at":"2026-07-05T04:28:36Z"},{"alias_kind":"pith_short_12","alias_value":"ALQ4BQAY4COA","created_at":"2026-07-05T04:28:36Z"},{"alias_kind":"pith_short_16","alias_value":"ALQ4BQAY4COAYOYM","created_at":"2026-07-05T04:28:36Z"},{"alias_kind":"pith_short_8","alias_value":"ALQ4BQAY","created_at":"2026-07-05T04:28:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:ALQ4BQAY4COAYOYMQTLQ4YZYZM","target":"record","payload":{"canonical_record":{"source":{"id":"2206.01096","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-06-02T15:22:29Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"0b9b29ea0c51b0fb49b1eaceef398ec88bd5cae4b21170f45314a953b70c3c81","abstract_canon_sha256":"e0e9a0f5188939c1a4e2d396d6ee115b529585f22639ed7900529d834735927b"},"schema_version":"1.0"},"canonical_sha256":"02e1c0c018e09c0c3b0c84d70e6338cb24cebcaff76ed238a978dac87874fb7a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:28:36.894960Z","signature_b64":"ux97TvJanEfu4YXcNwqYF6KmPlgq/gSPJb5IO0OatjjLZ8VACKCb6P1CCU/jG1c2AYsSHom2xGpp6xzntdusDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"02e1c0c018e09c0c3b0c84d70e6338cb24cebcaff76ed238a978dac87874fb7a","last_reissued_at":"2026-07-05T04:28:36.894489Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:28:36.894489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2206.01096","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":"2026-07-05T04:28:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YUDXej6iCKHH3tR1Qg8E0hTyHZxCb2yMUj9jYBn4PDliXbVqU5N03Fah4GSUWci3oKDpyJ+TFYqIns6wV7H1Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T09:23:44.274633Z"},"content_sha256":"1c0f735373b1c7b23a15d00419a474414205a18144a5b1dabac0edcf2eb1768d","schema_version":"1.0","event_id":"sha256:1c0f735373b1c7b23a15d00419a474414205a18144a5b1dabac0edcf2eb1768d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:ALQ4BQAY4COAYOYMQTLQ4YZYZM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Dual-fusion Semantic Segmentation Framework With GAN For SAR Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Andi Zhang, Donghui Li, Fang Liu, Jia Liu, Jiao Shi, Wenfei Gao, Wenhua Zhang","submitted_at":"2022-06-02T15:22:29Z","abstract_excerpt":"Deep learning based semantic segmentation is one of the popular methods in remote sensing image segmentation. In this paper, a network based on the widely used encoderdecoder architecture is proposed to accomplish the synthetic aperture radar (SAR) images segmentation. With the better representation capability of optical images, we propose to enrich SAR images with generated optical images via the generative adversative network (GAN) trained by numerous SAR and optical images. These optical images can be used as expansions of original SAR images, thus ensuring robust result of segmentation. Th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.01096","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/2206.01096/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":"2026-07-05T04:28:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Pkrc4ysjqn76/z/1JwJThG8S1Dx2RPZxuVqtbBa5id4KR4EkWBduCX4grS8vvjjDgWdlMekDqPNQ9V4l6ugLBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T09:23:44.275260Z"},"content_sha256":"d6fc2391d5077f10ba29a1e9956e56575c8237c48ed7e1fb2dabdb39b1a98986","schema_version":"1.0","event_id":"sha256:d6fc2391d5077f10ba29a1e9956e56575c8237c48ed7e1fb2dabdb39b1a98986"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ALQ4BQAY4COAYOYMQTLQ4YZYZM/bundle.json","state_url":"https://pith.science/pith/ALQ4BQAY4COAYOYMQTLQ4YZYZM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ALQ4BQAY4COAYOYMQTLQ4YZYZM/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":"2026-08-04T09:23:44Z","links":{"resolver":"https://pith.science/pith/ALQ4BQAY4COAYOYMQTLQ4YZYZM","bundle":"https://pith.science/pith/ALQ4BQAY4COAYOYMQTLQ4YZYZM/bundle.json","state":"https://pith.science/pith/ALQ4BQAY4COAYOYMQTLQ4YZYZM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ALQ4BQAY4COAYOYMQTLQ4YZYZM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:ALQ4BQAY4COAYOYMQTLQ4YZYZM","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":"e0e9a0f5188939c1a4e2d396d6ee115b529585f22639ed7900529d834735927b","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-06-02T15:22:29Z","title_canon_sha256":"0b9b29ea0c51b0fb49b1eaceef398ec88bd5cae4b21170f45314a953b70c3c81"},"schema_version":"1.0","source":{"id":"2206.01096","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2206.01096","created_at":"2026-07-05T04:28:36Z"},{"alias_kind":"arxiv_version","alias_value":"2206.01096v1","created_at":"2026-07-05T04:28:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2206.01096","created_at":"2026-07-05T04:28:36Z"},{"alias_kind":"pith_short_12","alias_value":"ALQ4BQAY4COA","created_at":"2026-07-05T04:28:36Z"},{"alias_kind":"pith_short_16","alias_value":"ALQ4BQAY4COAYOYM","created_at":"2026-07-05T04:28:36Z"},{"alias_kind":"pith_short_8","alias_value":"ALQ4BQAY","created_at":"2026-07-05T04:28:36Z"}],"graph_snapshots":[{"event_id":"sha256:d6fc2391d5077f10ba29a1e9956e56575c8237c48ed7e1fb2dabdb39b1a98986","target":"graph","created_at":"2026-07-05T04:28:36Z","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/2206.01096/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning based semantic segmentation is one of the popular methods in remote sensing image segmentation. In this paper, a network based on the widely used encoderdecoder architecture is proposed to accomplish the synthetic aperture radar (SAR) images segmentation. With the better representation capability of optical images, we propose to enrich SAR images with generated optical images via the generative adversative network (GAN) trained by numerous SAR and optical images. These optical images can be used as expansions of original SAR images, thus ensuring robust result of segmentation. Th","authors_text":"Andi Zhang, Donghui Li, Fang Liu, Jia Liu, Jiao Shi, Wenfei Gao, Wenhua Zhang","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-06-02T15:22:29Z","title":"A Dual-fusion Semantic Segmentation Framework With GAN For SAR Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2206.01096","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":"sha256:1c0f735373b1c7b23a15d00419a474414205a18144a5b1dabac0edcf2eb1768d","target":"record","created_at":"2026-07-05T04:28:36Z","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":"e0e9a0f5188939c1a4e2d396d6ee115b529585f22639ed7900529d834735927b","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2022-06-02T15:22:29Z","title_canon_sha256":"0b9b29ea0c51b0fb49b1eaceef398ec88bd5cae4b21170f45314a953b70c3c81"},"schema_version":"1.0","source":{"id":"2206.01096","kind":"arxiv","version":1}},"canonical_sha256":"02e1c0c018e09c0c3b0c84d70e6338cb24cebcaff76ed238a978dac87874fb7a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"02e1c0c018e09c0c3b0c84d70e6338cb24cebcaff76ed238a978dac87874fb7a","first_computed_at":"2026-07-05T04:28:36.894489Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:28:36.894489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ux97TvJanEfu4YXcNwqYF6KmPlgq/gSPJb5IO0OatjjLZ8VACKCb6P1CCU/jG1c2AYsSHom2xGpp6xzntdusDw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:28:36.894960Z","signed_message":"canonical_sha256_bytes"},"source_id":"2206.01096","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1c0f735373b1c7b23a15d00419a474414205a18144a5b1dabac0edcf2eb1768d","sha256:d6fc2391d5077f10ba29a1e9956e56575c8237c48ed7e1fb2dabdb39b1a98986"],"state_sha256":"b2d574c9d71ce863538745c229bf998727dbb526a97adbcfbd19994a233e59da"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zFIFmwK9Ke0QINtZ4La9SPU8Fna6Coa3ejxn3TqNyOVtK2KQPZCCPdVts+gcAH5NIndRqg+WtGI2idbEmTjTBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T09:23:44.278764Z","bundle_sha256":"c2b8e3d6289d5300438e087449ea36ed3c74377f0b762dab78d60e61950289bd"}}