{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:EVXC3ODU2ZMZUVROLC2X3KLZJI","short_pith_number":"pith:EVXC3ODU","canonical_record":{"source":{"id":"1812.05329","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-13T09:27:12Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"65af291716274eaab160ae256bf33d1d0cea6bdf43708d5ea26f123b6bbe1cd7","abstract_canon_sha256":"8bb093d905d475cd0330115e0de760472c8063898db4b7c551b5d9f1cb88e5f6"},"schema_version":"1.0"},"canonical_sha256":"256e2db874d6599a562e58b57da9794a296f549a4bf0941fa268f826446fda36","source":{"kind":"arxiv","id":"1812.05329","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.05329","created_at":"2026-05-17T23:57:07Z"},{"alias_kind":"arxiv_version","alias_value":"1812.05329v2","created_at":"2026-05-17T23:57:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.05329","created_at":"2026-05-17T23:57:07Z"},{"alias_kind":"pith_short_12","alias_value":"EVXC3ODU2ZMZ","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"EVXC3ODU2ZMZUVRO","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"EVXC3ODU","created_at":"2026-05-18T12:32:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:EVXC3ODU2ZMZUVROLC2X3KLZJI","target":"record","payload":{"canonical_record":{"source":{"id":"1812.05329","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-13T09:27:12Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"65af291716274eaab160ae256bf33d1d0cea6bdf43708d5ea26f123b6bbe1cd7","abstract_canon_sha256":"8bb093d905d475cd0330115e0de760472c8063898db4b7c551b5d9f1cb88e5f6"},"schema_version":"1.0"},"canonical_sha256":"256e2db874d6599a562e58b57da9794a296f549a4bf0941fa268f826446fda36","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:57:07.220223Z","signature_b64":"YcJ10BkiIv5Z39e6KnGE71mYJSU47aTmLW0a7YmUeMzMZkaw/ML6kKNuJflMBI00Ak2qZAIA1xSziE0gt2xMCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"256e2db874d6599a562e58b57da9794a296f549a4bf0941fa268f826446fda36","last_reissued_at":"2026-05-17T23:57:07.219762Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:57:07.219762Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.05329","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":"2026-05-17T23:57:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jT3m3aAf+eeJWNaJ6cURW1kHvLgDV3M/vpdlhlxi33uZYc0TIGm1XZ7832ip/yioqjEkh8zyfQSNQjSIXrzZDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T18:59:13.581150Z"},"content_sha256":"c4bc903cf4b04f9b75ba85e47f214b91a1d0b9d2095070d57be2069b0113b6ac","schema_version":"1.0","event_id":"sha256:c4bc903cf4b04f9b75ba85e47f214b91a1d0b9d2095070d57be2069b0113b6ac"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:EVXC3ODU2ZMZUVROLC2X3KLZJI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Wider Channel Attention Network for Remote Sensing Image Super-resolution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Guangluan Xu, Jun Gu, Lei Wang, Ran Wen, Xian Sun, Yue Zhang","submitted_at":"2018-12-13T09:27:12Z","abstract_excerpt":"Recently, deep convolutional neural networks (CNNs) have obtained promising results in image processing tasks including super-resolution (SR). However, most CNN-based SR methods treat low-resolution (LR) inputs and features equally across channels, rarely notice the loss of information flow caused by the activation function and fail to leverage the representation ability of CNNs. In this letter, we propose a novel single-image super-resolution (SISR) algorithm named Wider Channel Attention Network (WCAN) for remote sensing images. Firstly, the channel attention mechanism is used to adaptively "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.05329","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":"2026-05-17T23:57:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KL5vuCHsTnMxJEENNPRqmc0HUJOfBUXLYLC2VXON21+il68rdeQJGksk5B6dTyHwX9q3rkvqCFT2EadqKlwwAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-27T18:59:13.581508Z"},"content_sha256":"8908e09e4fc95432c8d27b44958c1e4a5518ddcfbc61db0311d2a802ed6737ba","schema_version":"1.0","event_id":"sha256:8908e09e4fc95432c8d27b44958c1e4a5518ddcfbc61db0311d2a802ed6737ba"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EVXC3ODU2ZMZUVROLC2X3KLZJI/bundle.json","state_url":"https://pith.science/pith/EVXC3ODU2ZMZUVROLC2X3KLZJI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EVXC3ODU2ZMZUVROLC2X3KLZJI/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":"2026-06-27T18:59:13Z","links":{"resolver":"https://pith.science/pith/EVXC3ODU2ZMZUVROLC2X3KLZJI","bundle":"https://pith.science/pith/EVXC3ODU2ZMZUVROLC2X3KLZJI/bundle.json","state":"https://pith.science/pith/EVXC3ODU2ZMZUVROLC2X3KLZJI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EVXC3ODU2ZMZUVROLC2X3KLZJI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:EVXC3ODU2ZMZUVROLC2X3KLZJI","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":"8bb093d905d475cd0330115e0de760472c8063898db4b7c551b5d9f1cb88e5f6","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-13T09:27:12Z","title_canon_sha256":"65af291716274eaab160ae256bf33d1d0cea6bdf43708d5ea26f123b6bbe1cd7"},"schema_version":"1.0","source":{"id":"1812.05329","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.05329","created_at":"2026-05-17T23:57:07Z"},{"alias_kind":"arxiv_version","alias_value":"1812.05329v2","created_at":"2026-05-17T23:57:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.05329","created_at":"2026-05-17T23:57:07Z"},{"alias_kind":"pith_short_12","alias_value":"EVXC3ODU2ZMZ","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"EVXC3ODU2ZMZUVRO","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"EVXC3ODU","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:8908e09e4fc95432c8d27b44958c1e4a5518ddcfbc61db0311d2a802ed6737ba","target":"graph","created_at":"2026-05-17T23:57:07Z","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":"Recently, deep convolutional neural networks (CNNs) have obtained promising results in image processing tasks including super-resolution (SR). However, most CNN-based SR methods treat low-resolution (LR) inputs and features equally across channels, rarely notice the loss of information flow caused by the activation function and fail to leverage the representation ability of CNNs. In this letter, we propose a novel single-image super-resolution (SISR) algorithm named Wider Channel Attention Network (WCAN) for remote sensing images. Firstly, the channel attention mechanism is used to adaptively ","authors_text":"Guangluan Xu, Jun Gu, Lei Wang, Ran Wen, Xian Sun, Yue Zhang","cross_cats":["eess.IV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-13T09:27:12Z","title":"Wider Channel Attention Network for Remote Sensing Image Super-resolution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.05329","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:c4bc903cf4b04f9b75ba85e47f214b91a1d0b9d2095070d57be2069b0113b6ac","target":"record","created_at":"2026-05-17T23:57:07Z","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":"8bb093d905d475cd0330115e0de760472c8063898db4b7c551b5d9f1cb88e5f6","cross_cats_sorted":["eess.IV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-13T09:27:12Z","title_canon_sha256":"65af291716274eaab160ae256bf33d1d0cea6bdf43708d5ea26f123b6bbe1cd7"},"schema_version":"1.0","source":{"id":"1812.05329","kind":"arxiv","version":2}},"canonical_sha256":"256e2db874d6599a562e58b57da9794a296f549a4bf0941fa268f826446fda36","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"256e2db874d6599a562e58b57da9794a296f549a4bf0941fa268f826446fda36","first_computed_at":"2026-05-17T23:57:07.219762Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:57:07.219762Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YcJ10BkiIv5Z39e6KnGE71mYJSU47aTmLW0a7YmUeMzMZkaw/ML6kKNuJflMBI00Ak2qZAIA1xSziE0gt2xMCQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:57:07.220223Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.05329","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4bc903cf4b04f9b75ba85e47f214b91a1d0b9d2095070d57be2069b0113b6ac","sha256:8908e09e4fc95432c8d27b44958c1e4a5518ddcfbc61db0311d2a802ed6737ba"],"state_sha256":"3b33ff8a3f9f4adcd653b99628c260b01dad3b0aedec1c45f49dc78e07be2801"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ei7qfiw90OlD5Zj4Z5Ah7h7Lstm/nNlyI2jZXJ4P+I8t5HwPW9Ym7PH1HRU3sa9fabGlq0muTa0dLqQtA+wIBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-27T18:59:13.583453Z","bundle_sha256":"3043afc63bdfc5ca31f22bde0ed4dafcecc2f4f140709bb262955a172c45feef"}}