Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:44:25.088956Z
Paper Citation Record · LEDGER
As of 22 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2505.06576.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:44:25.088956Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
68 of 68 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 2ec553b5-b836-4b10-be46-a5f991ca1054 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Perceptual quality assessment of pan-sharpened images
Reference 1
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Observation 9cf6961a-6e15-4d85-9dc6-67463cf4da59 · outbound
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Reference 2
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Observation 69b723bc-7154-4ff1-9f91-62ede8d4e8e2 · outbound
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Reference 3
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Observation 87af3442-67fd-4871-9c36-4fd997d6fcb9 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening ResPanDiff: Diffusion Model for Pansharpening by Inferring Residual Inference
Reference 4
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Observation c5a0ad8f-f308-41ee-9d52-4b938e972e80 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Pancsc-net: A model-driven deep unfolding method for pansharpening
Reference 5
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Observation 4433273b-7553-49d8-9102-c858c0117b65 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening A New Adaptive Component-Substitution-Based Satellite Image Fusion by Using Partial Replacement
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Two-Stage Random Alternation Framework for One-Shot Pansharpening Detail injection-based deep convolutional neural networks for pansharpening
Reference 9
Source-reported events for the cited work
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Observation 1dde5266-f3fe-4a97-878c-3ad0b4619551 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Detail Injection-Based Deep Convolutional Neural Networks for Pansharpening
Reference 10
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Observation 83552aa9-1c2f-4751-a8b1-6f3f23326c94 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Paoletti, Giuseppe Scarpa, Jiang He, Yongjun Zhang, Jocelyn Chanussot, and Antonio Plaza
Reference 11
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Observation a923a9f6-fcd3-417d-b3ef-d5e268f5538d · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Content-adaptive non-local convolution for remote sensing pansharpening
Reference 12
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Observation 1fdaf320-4faa-4274-a18f-cc99424af475 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening A variational pan-sharpening with local gradient constraints
Reference 13
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Observation a53584b9-209c-4d0a-ba71-7d1f5658a937 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening A Variational Pan-Sharpening With Local Gradient Constraints
Reference 14
Source-reported events for the cited work
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Observation e941e5cc-e74e-49a5-b189-c8f616625e25 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Cross-scale domain adaptation with comprehensive information for pansharpening
Reference 15
Source-reported events for the cited work
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Observation 5e7965d6-06b0-4639-8311-601da6fee25f · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Panchromatic and multi-spectral image fusion for new satellites based on multi-channel deep model
Reference 16
Source-reported events for the cited work
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Observation 653d9d38-6b68-4824-8cb1-4f4d28d59b9e · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Pan-mamba: Effective pan-sharpening with state space model
Reference 17
Source-reported events for the cited work
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Observation e84811b4-6b91-4062-ad6f-a141d0b47cf8 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Lagconv: Local- context adaptive convolution kernels with global harmonic bias for pansharpening
Reference 18
Source-reported events for the cited work
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Observation c9f038d3-9fcd-4d94-b932-d872d2e2b022 · outbound
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Reference 19
Source-reported events for the cited work
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Observation d80052f5-6d96-44da-96d3-62614e02194d · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Remote sensing image fusion via sparse representations over learned dictionaries
Reference 20
Source-reported events for the cited work
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Observation 8aba0505-fe94-4ab8-a8c7-d4cc711ce2bc · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Ddcgan: A dual-discriminator conditional generative adversarial network for multi-resolution image fusion
Reference 21
Source-reported events for the cited work
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Observation 58f32bd1-3bfd-4a66-a9a3-8582990df208 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Pan-gan: An unsupervised pan-sharpening method for remote sensing image fusion
Reference 22
Source-reported events for the cited work
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Observation ff31e882-7357-4ef8-9a26-947f1d67b961 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Pansharpening by convolutional neural networks
Reference 24
Source-reported events for the cited work
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Observation e60611a8-414b-40a6-8e01-d1d9caa8ed71 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Review of the pansharpening methods for remote sensing images based on the idea of meta-analysis: Practical discussion and challenges
Reference 25
Source-reported events for the cited work
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Observation 1848ab9c-a506-471e-b770-c8cdb556233e · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Sveinsson, and Magnus O
Reference 26
Source-reported events for the cited work
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Observation 46315c1f-b6d9-4749-b0fc-bc284cb2c413 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Pansharpening techniques: Optimizing the loss function for convolutional neural networks
Reference 27
Source-reported events for the cited work
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Observation 39f5aa08-e8ff-4b9c-bd03-582f29d4e589 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Unsupervised Hyperspectral Pansharpening via Low-rank Diffusion Model
Reference 28
Source-reported events for the cited work
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Observation 92e92c52-9538-4e9f-94a4-778d096f3f7c · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Variational zero-shot multispectral pansharpen- ing
Reference 29
Source-reported events for the cited work
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Observation 1d496b4b-05c3-4754-8c24-9f2c7c0bc887 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Full-resolution quality assessment for pansharpening
Reference 30
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Observation 16583966-27f6-4f9a-81e8-ae87af20e577 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening zero-shot
Reference 31
Source-reported events for the cited work
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Observation ee4552d3-f1b2-4934-bfc4-65a45db78ac3 · outbound
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Reference 32
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Observation ef62f7e3-fd66-417a-bc7c-f82a7a4efbd5 · outbound
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Reference 33
Source-reported events for the cited work
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Observation db0e2db7-cb7a-43fd-8b63-370dfb5e29dd · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening A detail-preserving cross-scale learning strategy for cnn-based pansharpening
Reference 34
Source-reported events for the cited work
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Observation 2f05cfa9-c658-468d-8f7c-61ad5a402642 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Robust band-dependent spatial-detail approaches for panchromatic sharpening
Reference 35
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Observation f1bb121d-49bd-4917-90e3-e75e12a8704a · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Robust Band-Dependent Spatial-Detail Approaches for Panchromatic Sharpening
Reference 36
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Observation 90a40252-07b1-4fed-8bf1-23594fa6c155 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Contrast and Error-Based Fusion Schemes for Multispectral Image Pansharpening
Reference 37
Source-reported events for the cited work
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Observation 7f9e2e1b-50e0-489f-b92c-621ac093e7a4 · outbound
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Reference 38
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Observation e85a6b6a-a50e-465b-bffb-0eb6172a7f7f · outbound
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Reference 39
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Observation 6408fe0b-8573-4662-91f9-85f20f7bf5ea · outbound
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Reference 40
Source-reported events for the cited work
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Observation 3b9f26f3-004f-4073-9886-5106e970c9a4 · outbound
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Reference 41
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Observation 618b4fcc-1ec2-4b0d-a4a1-15d0c1e652e6 · outbound
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Reference 42
Source-reported events for the cited work
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Observation b4444d5d-79b4-4273-a1f2-9d07a5103e3e · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Fusion of multispectral and panchromatic images via sparse representation and local autoregressive model
Reference 43
Source-reported events for the cited work
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Two-Stage Random Alternation Framework for One-Shot Pansharpening Boosting the accuracy of multi- spectral image pansharpening by learning a deep residual network
Reference 44
Source-reported events for the cited work
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Observation c1445ce4-e2aa-4429-8fc2-c7787734ce99 · outbound
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Reference 45
Source-reported events for the cited work
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Observation 128b16bc-a05d-432d-91d9-7b699ef3ce05 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening U2fusion: A unified unsupervised image fusion network
Reference 46
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Observation 71855445-d9d0-4917-88d6-edf3bf8c9235 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Panflownet: A flow-based deep network for pan-sharpening
Reference 47
Source-reported events for the cited work
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Observation 23df41a4-0292-4e67-8540-dfac49ee9d3f · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Cross-resolution semi-supervised adversarial learning for pansharpening
Reference 48
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Observation 176433ac-edaf-4343-983f-ec03b039c052 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Multi-scale spatial- spectral attention guided fusion network for pansharpening
Reference 49
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Two-Stage Random Alternation Framework for One-Shot Pansharpening Gtp-pnet: A residual learning network based on gradient transformation prior for pansharpening
Reference 50
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Reference 51
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Two-Stage Random Alternation Framework for One-Shot Pansharpening Lgpconv: Learnable gaussian perturbation convolution for lightweight pansharpening
Reference 52
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Observation b725e243-c1d9-44a3-b696-1059e6dc220f · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Perceppan: Towards unsupervised pan-sharpening based on perceptual loss
Reference 53
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Observation 302a7902-6d90-4956-8d12-e4aa4054a983 · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening The described methodology and experimental setup support the claims of robust, high-quality fusion and superior performance
Reference 54
Source-reported events for the cited work
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Observation 5643df43-dd17-4670-8a51-6ff87432f76a · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Limitations
Reference 55
Source-reported events for the cited work
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Two-Stage Random Alternation Framework for One-Shot Pansharpening However, an approximate analysis of the Degradation-Aware Modeling (DAM) capability to capture spectral degradation is provided in the supplementary material
Reference 56
Source-reported events for the cited work
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Reference 57
Source-reported events for the cited work
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Reference 58
Source-reported events for the cited work
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Observation 40709f92-1172-4b7d-8d8e-ba6518b67343 · outbound
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Reference 59
Source-reported events for the cited work
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Reference 60
Source-reported events for the cited work
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Reference 61
Source-reported events for the cited work
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Reference 62
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Two-Stage Random Alternation Framework for One-Shot Pansharpening Guidelines: • The answer NA means that there is no societal impact of the work performed
Reference 63
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Two-Stage Random Alternation Framework for One-Shot Pansharpening Guidelines: • The answer NA means that the paper poses no such risks
Reference 64
Source-reported events for the cited work
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Reference 65
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Two-Stage Random Alternation Framework for One-Shot Pansharpening Guidelines: • The answer NA means that the paper does not release new assets
Reference 66
Source-reported events for the cited work
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Reference 67
Source-reported events for the cited work
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Observation da7d60f6-75b7-4607-90da-e993350b947b · outbound
Two-Stage Random Alternation Framework for One-Shot Pansharpening Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects
Reference 68
Source-reported events for the cited work
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Reference 69
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
No inbound Pith citation observations are available.