{"as_of":"2026-08-09T06:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0c09c6ed26774567cdf00836d717a2b066dba1c13b9956b9cac4ee81a3f3d82d","coverage":[{"denominator":19,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":19,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:29:34.660763Z","state":"measured"},{"denominator":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.07779/citation-record","integrity":"/paper/2506.07779/integrity","json":"/paper/2506.07779/citation-record.json","paper":"/paper/2506.07779"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:35.045995Z","title":"Grounding dino: Marrying dino with grounded pre-training for open-set object detection,","venue":null,"work_id":"2dbd17aa-f9e9-4efe-ad57-9872c1009027","year":2024},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.543807Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:9135dbd64376bae157014f76380f31820ddbada5356a50da31c6f9c686ed2b17","observation_id":"8309cd8b-c0cf-40c0-a680-bdb659c3f01c","resolution":{"observed_at":"2026-08-07T05:29:35.053722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.551042Z","title":"Segment anything,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.551042Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:1bcb0c8215bcd6f1903028bcf840bbd14a68c85682fad521c3c56738aa1bdb78","observation_id":"b89fdfff-6071-447c-8c05-4966bd1f8bd5","resolution":{"observed_at":"2026-08-07T05:29:34.551042Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:35.013727Z","title":"Image fusion techniques: a survey,","venue":null,"work_id":"29953be9-07f5-4add-8785-b9291814db55","year":2021},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.557022Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:7196ff653d8095b7032dbed69da25ee30e00fa6b81e8a8e1d3b475f4323392cf","observation_id":"a55d49ea-5783-4aba-a722-a8aa55a4aa30","resolution":{"observed_at":"2026-08-07T05:29:35.019873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.992586Z","title":"Pa- fusion: A general image fusion network with adversarial representation learning,","venue":null,"work_id":"12eb0c20-77ce-4a32-8c1f-445bee7b9c8c","year":2025},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.563179Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:4bbf0227ea906d9797f7c3fd7f7736b3f7888c2bd82d2c30d246bd5a8a809ced","observation_id":"dffec129-9cf3-4006-9362-ecf375a81ac9","resolution":{"observed_at":"2026-08-07T05:29:34.999168Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.569984Z","title":"Image fusion in the loop of high-level vision tasks: A semantic-aware real-time infrared and visible image fusion network,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.569984Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:f8e865194a41209d53bf2923c3855b2e2a2e2f39ea76c9b40e1a6da953c7228d","observation_id":"48220f14-f074-4d5e-826e-2e580e5d5e1d","resolution":{"observed_at":"2026-08-07T05:29:34.569984Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.955681Z","title":"Detfusion: A detection-driven infrared and visible image fusion network,","venue":null,"work_id":"095c1631-f1f9-4527-92eb-d30fe60b57b0","year":2022},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.576993Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:686d7e326af29e1b365aa403c84250f6ebe726135f027486171fc08677864aeb","observation_id":"cf8d81d1-d50b-41a3-8d1e-af833911d693","resolution":{"observed_at":"2026-08-07T05:29:34.962738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.934690Z","title":"Sedrfuse: A symmetric encoder–decoder with residual block network for infrared and visible image fusion,","venue":null,"work_id":"bad9750d-6f07-4e18-9f51-ff03db6f79b2","year":2020},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.587539Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:76ddb7f60d952e0b3a91054ce6c150692ac83aa869a4d0be39af683c5423ca0a","observation_id":"a4740643-ce4e-48d2-8222-cbf89012aba4","resolution":{"observed_at":"2026-08-07T05:29:34.941128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.915833Z","title":"Mafusion: Multiscale attention network for infrared and visible image fusion,","venue":null,"work_id":"2d05e867-1b17-401c-ab61-a52b773dccd3","year":2022},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.594991Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:0886723ed84a4579ecf98fb4a8e0305959cac0b20ec18ebc1d85f9923abc8d4c","observation_id":"d90285b8-668c-445c-a092-1bb8acd017b2","resolution":{"observed_at":"2026-08-07T05:29:34.922201Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.893871Z","title":"Target-aware dual adversarial learning and a multi-scenario multi- modality benchmark to fuse infrared and visible for object detection,","venue":null,"work_id":"e8fa06cd-3029-4b6e-865b-56a579ccfeea","year":2022},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.601318Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:65ddd98046db6b4eaa1edaa5d77bffa21bd950be56fef92878ec9b458cda653f","observation_id":"8397e999-b75d-45cd-a769-7df5e4eeeff0","resolution":{"observed_at":"2026-08-07T05:29:34.900441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.872870Z","title":"Swinfusion: Cross-domain long-range learning for general image fusion via swin transformer,","venue":null,"work_id":"471095f3-526a-4a02-83a7-0fa7087319c4","year":2022},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.606584Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:4fb52a8fa9578f0b75c49908a2cdb9a3aef094fadc99b7d06b8db1f066bd7c5b","observation_id":"5b89b712-921e-41fa-ad9c-ebca23f530c2","resolution":{"observed_at":"2026-08-07T05:29:34.878714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.612144Z","title":"Cddfuse: Correlation-driven dual-branch feature decomposition for multi-modality image fusion,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.612144Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:77c128bcddaa8f7f6d00d6eae94d3b5c3a28995f5a30a3a51759182ccd1e068c","observation_id":"5c12cf9f-e207-408d-9eb4-2d52db7a94f5","resolution":{"observed_at":"2026-08-07T05:29:34.612144Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.838742Z","title":"Ydtr: Infrared and visible image fusion via y-shape dynamic transformer,","venue":null,"work_id":"3c6a77dc-ad08-431a-9747-c1fc8b05ce6f","year":2022},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.617317Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:48b7d262f2966dc15361a68b7ac05f7133b5bb0a175a839cf04f6d53870810e8","observation_id":"0d795748-5dd1-4fda-8515-ab522aae9d98","resolution":{"observed_at":"2026-08-07T05:29:34.846304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.623814Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.623814Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:9861a0114fba330f23a9889ae9718b681216b1cbcaac02bab3e1b272933319a1","observation_id":"69fc9179-fc97-4fa3-8dee-a2501138a900","resolution":{"observed_at":"2026-08-07T05:29:34.623814Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.801126Z","title":"Superfusion: A ver- satile image registration and fusion network with semantic awareness,","venue":null,"work_id":"6b1bb7b7-b5fb-481b-89d5-aced4aa60a41","year":2022},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.632071Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:7ae2a8960819bd78a138064f5966ef8b34c5d4efda1d1fb2f06e4356d1f22d02","observation_id":"1d5a4f81-2c9a-4eea-a1d1-7f3cf5131549","resolution":{"observed_at":"2026-08-07T05:29:34.810862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.777515Z","title":"De- terministic edge-preserving regularization in computed imaging,","venue":null,"work_id":"093d3c7f-3ffc-46c3-97fd-1727ed093772","year":1997},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.637238Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:467e417737a62c753103087dfed5de8af138a9d58fef30f2675abc36b317886c","observation_id":"c6b9380f-77e6-4006-be61-dae4615dfc51","resolution":{"observed_at":"2026-08-07T05:29:34.783988Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.642624Z","title":"Llvip: A visible-infrared paired dataset for low-light vision,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.642624Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:e0b24d9fbb8602d3b410ebb2ad856355f3dc6c6c0bc6e68ff76083a24ffb862c","observation_id":"2ba9ff59-7273-43bc-903b-ea79df26bf8a","resolution":{"observed_at":"2026-08-07T05:29:34.642624Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.735603Z","title":"Piafusion: A progres- sive infrared and visible image fusion network based on illumination aware,","venue":null,"work_id":"c9838e5a-a150-44b1-85f4-7197f029c28e","year":2022},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.648282Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:14c9eb8d87c9adaf1928f1cdad38de4092be220fb06dd5b3e0e4126818b3da3f","observation_id":"909352cf-d504-4c79-9505-6f0f4d236d64","resolution":{"observed_at":"2026-08-07T05:29:34.748681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.653754Z","title":"Swin transformer: Hierarchical vision transformer using shifted windows,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.653754Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:e17c7bcb04e39b26568336ec95c1b626b00dd7364d2965d3b313e137fc475f5c","observation_id":"47caf97b-ce04-4d41-ad5c-b5d922943a1c","resolution":{"observed_at":"2026-08-07T05:29:34.653754Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:29:34.660763Z","title":"Restormer: Efficient transformer for high-resolution image restoration,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:29:34.660763Z"},"links":{"citing_paper":"/paper/2506.07779"},"observation_digest":"sha256:18b4530fa2bda7a757220cea4d1862fd8dbfb1801b4e9d12840eb9190fa998c2","observation_id":"b035861b-a1ec-47c9-abb3-4f7840be961f","resolution":{"observed_at":"2026-08-07T05:29:34.660763Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.07779","last_updated":"2025-06-09T13:56:32Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T09:01:46.570221Z","submitted_at":"2025-06-09T13:56:32Z","title":"Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods"},"reference_resolution":{"displayed":19,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":12},"total_outbound_references":19},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2506.07779."}