Universal Pansharpening Model | Paper Citation Record

Observation 758423f3-e8ac-45c9-a353-c0854df84dc5 · outbound

This paper cites A semantic-enhanced multi-modal remote sensing foundation model for earth observation,.

Universal Pansharpening Model A semantic-enhanced multi-modal remote sensing foundation model for earth observation,

Reference 1

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Observation cd1d905a-4a8a-4394-b53d-e85257430395 · outbound

This paper cites Hipandas: Hyperspectral image joint denoising and super-resolution by image fusion with the panchromatic image,.

Universal Pansharpening Model Hipandas: Hyperspectral image joint denoising and super-resolution by image fusion with the panchromatic image,

Reference 2

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Observation c38badea-dafb-42a4-86c1-009a03799bcf · outbound

This paper cites Hyperspectral pansharpening: Critical review, tools, and future perspectives,.

Universal Pansharpening Model Hyperspectral pansharpening: Critical review, tools, and future perspectives,

Reference 3

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Observation 1a0ce516-f658-4af7-9e21-be5c282c889d · outbound

This paper cites Toward resolution mismatching: Modality-aware feature-aligned network for pan-sharpening,.

Universal Pansharpening Model Toward resolution mismatching: Modality-aware feature-aligned network for pan-sharpening,

Reference 4

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Observation 56291039-3a9a-4235-a292-3a9ea2abb46b · outbound

This paper cites Deep adaptive unfolded network via spatial morphology stripping and spectral filtration for pan-sharpening,.

Universal Pansharpening Model Deep adaptive unfolded network via spatial morphology stripping and spectral filtration for pan-sharpening,

Reference 5

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Observation be03511d-c4b9-454c-abfd-5126a1b4127e · outbound

This paper cites Hyperspectral image super- resolution meets deep learning: A survey and perspective,.

Universal Pansharpening Model Hyperspectral image super- resolution meets deep learning: A survey and perspective,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.405107Z

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Observation 6e019e25-7863-49ed-87b8-756f16160621 · outbound

This paper cites From classical image fusion to deep representation learning: A survey of the advances in hyperspectral image pan-sharpening,.

Universal Pansharpening Model From classical image fusion to deep representation learning: A survey of the advances in hyperspectral image pan-sharpening,

Reference 7

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Observation 6e4cc0ad-fe1d-40dd-be0b-d64af374b0c1 · outbound

This paper cites Robust band-dependent spatial-detail approaches for panchromatic sharpening,.

Universal Pansharpening Model Robust band-dependent spatial-detail approaches for panchromatic sharpening,

Reference 8

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Observation 4d301c86-af19-4f50-b67c-a3f15d65e281 · outbound

This paper cites Spatial methods for multispectral pansharpening: Multiresolution analysis demystified,.

Universal Pansharpening Model Spatial methods for multispectral pansharpening: Multiresolution analysis demystified,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.414040Z

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Observation 1168093a-36a2-422b-a977-4c3a65f48cc5 · outbound

This paper cites Better image filter for pansharp- ening,.

Universal Pansharpening Model Better image filter for pansharp- ening,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.417204Z

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Observation 4492efee-d579-43de-b12c-cddd5ff4fdb1 · outbound

This paper cites Progress and challenges in intelligent remote sens. satellite systems,.

Universal Pansharpening Model Progress and challenges in intelligent remote sens. satellite systems,

Reference 11

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Observation 206a7de0-1a3a-4b75-9e27-72c160e22394 · outbound

This paper cites A variational pan-sharpening with local gradient constraints,.

Universal Pansharpening Model A variational pan-sharpening with local gradient constraints,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.423042Z

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Observation 33bf3c8d-b998-49c4-9c8e-ed80e1472c79 · outbound

This paper cites An overview of gradient descent optimization algorithms.

Universal Pansharpening Model An overview of gradient descent optimization algorithms

Reference 13

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Observation 8772edf4-d627-42cd-9fe9-6eb63fbe5fe4 · outbound

This paper cites Panchromatic and multispectral image fusion for remote sens. and earth observation: Concepts, taxonomy, literature review, evaluation methodologies and challenges ahead,.

Universal Pansharpening Model Panchromatic and multispectral image fusion for remote sens. and earth observation: Concepts, taxonomy, literature review, evaluation methodologies and challenges ahead,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.428460Z

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Observation ba64b984-6d6c-42ee-b35e-fe6eaf699e7f · outbound

This paper cites P2sharpen: A progressive pansharpening network with deep spectral transformation,.

Universal Pansharpening Model P2sharpen: A progressive pansharpening network with deep spectral transformation,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.431077Z

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Observation 2e1409a6-463e-4d5f-828f-484c9ba1e96c · outbound

This paper cites From forgotten to pan-sharpening,.

Universal Pansharpening Model From forgotten to pan-sharpening,

Reference 16

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Observation bb27dcf8-e729-488c-a791-0f25da30f681 · outbound

This paper cites Upangan: Unsupervised pan- sharpening based on the spectral and spatial loss constrained generative adversarial network,.

Universal Pansharpening Model Upangan: Unsupervised pan- sharpening based on the spectral and spatial loss constrained generative adversarial network,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.436498Z

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Observation 2f99f22c-ec7a-441d-8e43-390e88a3635f · outbound

This paper cites Mft-gan: A multiscale feature- guided transformer network for unsupervised hyperspectral pansharpen- ing,.

Universal Pansharpening Model Mft-gan: A multiscale feature- guided transformer network for unsupervised hyperspectral pansharpen- ing,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.438850Z

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Observation 561791cb-199f-4085-a673-5b3f82e3d04d · outbound

This paper cites Linearly-evolved transformer for pan-sharpening,.

Universal Pansharpening Model Linearly-evolved transformer for pan-sharpening,

Reference 19

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Observation 722fd0b1-8689-43e8-a77c-1ad9293a72e0 · outbound

This paper cites Transformer-ensemble based implicit spectral-spatial functions for arbitrary-resolution hyperspectral pansharpening,.

Universal Pansharpening Model Transformer-ensemble based implicit spectral-spatial functions for arbitrary-resolution hyperspectral pansharpening,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.444272Z

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Observation 584f6233-2a75-4a12-8aa5-af4cd50e6cf7 · outbound

This paper cites Pan-mamba: Effective pan-sharpening with state space model,.

Universal Pansharpening Model Pan-mamba: Effective pan-sharpening with state space model,

Reference 21

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Observation e316d0f4-0915-4f14-b37b-c24927d65684 · outbound

This paper cites Mambamtl: Progressive mutual- guided mamba multi-task learning for hyperspectral image pansharpen- ing and classification,.

Universal Pansharpening Model Mambamtl: Progressive mutual- guided mamba multi-task learning for hyperspectral image pansharpen- ing and classification,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.450196Z

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Observation bd2a0db0-8c19-4d34-90b8-13b792c7fc70 · outbound

This paper cites Zero-sharpen: A universal pansharpening method across satellites for reducing scale-variance gap via zero-shot variation,.

Universal Pansharpening Model Zero-sharpen: A universal pansharpening method across satellites for reducing scale-variance gap via zero-shot variation,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.452872Z

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Observation 86ab0313-2f5c-46f9-803d-017f11eeb86c · outbound

This paper cites Hyperspectral pansharpening via diffusion models with iteratively zero- shot guidance,.

Universal Pansharpening Model Hyperspectral pansharpening via diffusion models with iteratively zero- shot guidance,

Reference 24

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Observation 650052f5-3323-4358-8f97-e788ad46b5ad · outbound

This paper cites Zero-shot semi- supervised learning for pansharpening,.

Universal Pansharpening Model Zero-shot semi- supervised learning for pansharpening,

Reference 25

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Observation 24a11eae-28e9-4d02-8667-d294e196f234 · outbound

This paper cites Enpowering your pansharpening models with generalizability: Unified distribution is all you need,.

Universal Pansharpening Model Enpowering your pansharpening models with generalizability: Unified distribution is all you need,

Reference 26

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Observation ddec7a32-23be-4e22-88ab-e9d258cb8d59 · outbound

This paper cites Rethinking pan-sharpening: A new training process for full-resolution generalization,.

Universal Pansharpening Model Rethinking pan-sharpening: A new training process for full-resolution generalization,

Reference 27

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Observation cdf958c0-3c7a-4dbd-a597-b2ffb985177f · outbound

This paper cites A survey on mixture of experts in large language models,.

Universal Pansharpening Model A survey on mixture of experts in large language models,

Reference 28

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Observation ed84537f-a23c-4def-9298-004f481e3fe9 · outbound

This paper cites Vitpose++: Vision transformer for generic body pose estimation,.

Universal Pansharpening Model Vitpose++: Vision transformer for generic body pose estimation,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.540173Z

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Observation 1d9dfd16-b263-4123-9d1c-1713bb2336e5 · outbound

This paper cites EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate.

Universal Pansharpening Model EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.543093Z

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Observation 1bde8d66-8812-4cfd-b06f-f81d0aa5469a · outbound

This paper cites Mixture of lora experts,.

Universal Pansharpening Model Mixture of lora experts,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.546651Z

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Observation 45314fb4-18bb-41b1-927d-d722a3d2ef11 · outbound

This paper cites Dense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models.

Universal Pansharpening Model Dense Training, Sparse Inference: Rethinking Training of Mixture-of-Experts Language Models

Reference 32

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Observation 05659a33-61ed-483a-a51f-a238975cafb0 · outbound

This paper cites Deepspeed-moe: Advancing mixture-of-experts inference and training to power next-generation ai scale,.

Universal Pansharpening Model Deepspeed-moe: Advancing mixture-of-experts inference and training to power next-generation ai scale,

Reference 33

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Observation 2f4877cf-187e-4415-8236-0aed5bff31d1 · outbound

This paper cites Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models.

Universal Pansharpening Model Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.555354Z

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Observation 027ab265-9bd7-4694-992e-e7815c42cf8f · outbound

This paper cites Base layers: Simplifying training of large, sparse models,.

Universal Pansharpening Model Base layers: Simplifying training of large, sparse models,

Reference 35

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Observation 45a43177-b98f-457f-9416-0935bb8b4cd8 · outbound

This paper cites Mixtral of Experts.

Universal Pansharpening Model Mixtral of Experts

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.561535Z

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Observation a75de75f-2fc7-4c7f-a240-f9e1b372e2ba · outbound

This paper cites Jamba: Hybrid transformer-mamba language models,.

Universal Pansharpening Model Jamba: Hybrid transformer-mamba language models,

Reference 37

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Observation e6415e5e-5442-4927-ba76-95dcfb1e9c6d · outbound

This paper cites Yuan 2.0-M32: Mixture of Experts with Attention Router.

Universal Pansharpening Model Yuan 2.0-M32: Mixture of Experts with Attention Router

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.568283Z

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Observation cbd4f9fb-7741-40cf-aea3-80b4d0ebeea7 · outbound

This paper cites PanGu-{\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing.

Universal Pansharpening Model PanGu-{\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.571719Z

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Observation eaa893d7-3409-416f-a904-5d639ad4300b · outbound

This paper cites Hmoe: Heterogeneous mixture of experts for language modeling,.

Universal Pansharpening Model Hmoe: Heterogeneous mixture of experts for language modeling,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.575317Z

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Observation cd538395-364c-46b5-9387-ae33dfeb035c · outbound

This paper cites Uni-moe: Scaling unified multimodal llms with mixture of experts,.

Universal Pansharpening Model Uni-moe: Scaling unified multimodal llms with mixture of experts,

Reference 41

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Observation 128afa29-ec5f-4907-b28b-46efa3bdde94 · outbound

This paper cites A new look at ihs-like image fusion methods,.

Universal Pansharpening Model A new look at ihs-like image fusion methods,

Reference 42

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Observation 65500dff-80e3-4b30-9661-3b75a8baa7dc · outbound

This paper cites Haze correction for contrast-based multispectral pansharpening,.

Universal Pansharpening Model Haze correction for contrast-based multispectral pansharpening,

Reference 43

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Observation 45b68126-ebf1-4b2e-a10e-d899ade3913d · outbound

This paper cites Improving component substitution pansharpening through multivariate regression of ms+pan data,.

Universal Pansharpening Model Improving component substitution pansharpening through multivariate regression of ms+pan data,

Reference 44

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Observation e0255f9a-2937-46ab-abd5-3a61f2cce38e · outbound

This paper cites Introduction of sensor spectral response into image fusion methods. application to wavelet-based methods,.

Universal Pansharpening Model Introduction of sensor spectral response into image fusion methods. application to wavelet-based methods,

Reference 45

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Observation 0af7c1b3-c5e4-4fdb-972b-5110bfd5f3dc · outbound

This paper cites Implementation of image fusion algorithm using matlab (laplacian pyramid),.

Universal Pansharpening Model Implementation of image fusion algorithm using matlab (laplacian pyramid),

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.592522Z

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Observation 4c018a6c-16ef-4c96-9317-f64970873c57 · outbound

This paper cites A critical comparison among pansharpening algorithms,.

Universal Pansharpening Model A critical comparison among pansharpening algorithms,

Reference 47

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Observation a1693bae-0bb9-4302-a9a9-d61d3d13a97f · outbound

This paper cites A variational model for p+ xs image fusion,.

Universal Pansharpening Model A variational model for p+ xs image fusion,

Reference 48

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Observation 98153819-8f6f-40d7-ad9c-d28ab9b0dfa1 · outbound

This paper cites Sirf: Simultaneous satellite image registration and fusion in a unified framework,.

Universal Pansharpening Model Sirf: Simultaneous satellite image registration and fusion in a unified framework,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.601519Z

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Observation d3d0c9e6-8628-4e67-a530-a7a65c3edafa · outbound

This paper cites A unified pansharpening model based on band-adaptive gradient and detail correction,.

Universal Pansharpening Model A unified pansharpening model based on band-adaptive gradient and detail correction,

Reference 50

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Observation 344838e8-2243-4497-be4e-cea8d2e6e0d0 · outbound

This paper cites Pansharpening by convolutional neural networks,.

Universal Pansharpening Model Pansharpening by convolutional neural networks,

Reference 51

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Observation 9d433969-65fb-4d55-a5e3-e6a3c6852ea8 · outbound

This paper cites Pannet: A deep network architecture for pan-sharpening,.

Universal Pansharpening Model Pannet: A deep network architecture for pan-sharpening,

Reference 52

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Observation 90c9cf5e-8d75-41fa-a169-16499951183c · outbound

This paper cites Panformer: A transformer based model for pan-sharpening,.

Universal Pansharpening Model Panformer: A transformer based model for pan-sharpening,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.612087Z

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Observation 5aa5433b-48c9-40a9-82f1-255c33f3142d · outbound

This paper cites Pan-mamba: Effective pan-sharpening with state space model,.

Universal Pansharpening Model Pan-mamba: Effective pan-sharpening with state space model,

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.614523Z

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Observation 60fe3440-6199-405c-b067-e9eb6f4714b8 · outbound

This paper cites Diffusion model with disentangled modulations for sharpening multispectral and hyperspectral images,.

Universal Pansharpening Model Diffusion model with disentangled modulations for sharpening multispectral and hyperspectral images,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.617648Z

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Observation 3aad13e3-7b06-4bb1-89c1-827d6537c609 · outbound

This paper cites A general spatial-frequency learning framework for multimodal image fusion,.

Universal Pansharpening Model A general spatial-frequency learning framework for multimodal image fusion,

Reference 56

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Observation 95dadac8-a506-4a5d-8e39-1abb968803d6 · outbound

This paper cites Deep spatial–spectral fusion transformer for remote sens. pansharpening,.

Universal Pansharpening Model Deep spatial–spectral fusion transformer for remote sens. pansharpening,

Reference 57

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Observation cae4d3d1-2e07-4187-a516-be321498c773 · outbound

This paper cites Cslp: A novel pansharpening method based on compressed sensing and l-pnn,.

Universal Pansharpening Model Cslp: A novel pansharpening method based on compressed sensing and l-pnn,

Reference 58

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Observation 5f06b279-603d-4202-ab5d-29184b760a1d · outbound

This paper cites Enhanced pansharpening via quaternion spatial-spectral interactions,.

Universal Pansharpening Model Enhanced pansharpening via quaternion spatial-spectral interactions,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.627667Z

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Observation c59a43b7-2a8b-4364-9b80-f0f5edf3915d · outbound

This paper cites Pan-sharpening via multiscale dynamic convolutional neural network,.

Universal Pansharpening Model Pan-sharpening via multiscale dynamic convolutional neural network,

Reference 60

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Observation 679d88e3-4119-4607-aad1-15db3e5d6316 · outbound

This paper cites Memory- augmented deep conditional unfolding network for pan-sharpening,.

Universal Pansharpening Model Memory- augmented deep conditional unfolding network for pan-sharpening,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-02T19:05:48.633695Z

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Observation 8edbcaa3-d9c1-485e-b9ab-5713561448ad · outbound

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Universal Pansharpening Model Pan-gan: An unsupervised pan-sharpening method for remote sens. image fusion,

Reference 62

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Universal Pansharpening Model Ssdiff: Spatial- spectral integrated diffusion model for remote sens. pansharpening,

Reference 63

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Reference 64

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Reference 65

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Universal Pansharpening Model A survey on vision transformer,

Reference 66

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Universal Pansharpening Model Bidirectional diffusion bridge models,

Reference 67

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Universal Pansharpening Model Residual Diffusion Bridge Model for Image Restoration

Reference 68

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Universal Pansharpening Model Tweedie’s formula and selection bias,

Reference 69

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Universal Pansharpening Model Diffusion posterior sampling for general noisy inverse problems,

Reference 70

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Universal Pansharpening Model Back to Basics: Let Denoising Generative Models Denoise

Reference 71

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Universal Pansharpening Model Rewrite the stars,

Reference 72

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Universal Pansharpening Model Smoothing filter-based intensity modulation: A spectral preserve image fusion technique for improving spatial details,

Reference 73

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Universal Pansharpening Model Mtf- tailored multiscale fusion of high-resolution ms and pan imagery,

Reference 74

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Universal Pansharpening Model A new adaptive component-substitution- based satellite image fusion by using partial replacement,

Reference 75

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Universal Pansharpening Model Pansharpening of multispectral images based on nonlocal parameter optimization,

Reference 76

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Universal Pansharpening Model Fusion of multispectral and panchromatic images based on morphological operators,

Reference 77

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Universal Pansharpening Model Deep gradient projection networks for pan-sharpening,

Reference 78

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Universal Pansharpening Model U2net: A general framework with spatial-spectral-integrated double u-net for image fusion,

Reference 79

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Universal Pansharpening Model Panflownet: A flow-based deep network for pan-sharpening,

Reference 80

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Universal Pansharpening Model Deep unfolded network with intrinsic supervision for pan-sharpening,

Reference 81

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Universal Pansharpening Model Content-adaptive non- local convolution for remote sens. pansharpening,

Reference 82

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Universal Pansharpening Model Paps: Progressive attention- based pan-sharpening,

Reference 83

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Universal Pansharpening Model Wavelet- assisted multi-frequency attention network for pansharpening,

Reference 84

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Universal Pansharpening Model Scope of validity of psnr in im- age/video quality assessment,

Reference 85

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Universal Pansharpening Model Image quality assessment: from error visibility to structural similarity,

Reference 86

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Universal Pansharpening Model Wald,Data fusion: definitions and architectures: fusion of images of different spatial resolutions

Reference 87

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Universal Pansharpening Model Comparison of pansharpening algorithms: Outcome of the 2006 grs-s data-fusion contest,

Reference 88

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Universal Pansharpening Model Multispectral and panchromatic data fusion assessment without refer- ence,

Reference 89

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Universal Pansharpening Model Fully convolutional networks for semantic segmentation,

Reference 90

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Observation ad12a6ef-0bbb-4049-ae85-e0c8279c9d98 · outbound

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Universal Pansharpening Model Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 91

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Universal Pansharpening Model Red and photographic infrared linear combinations for monitoring vegetation,

Reference 92

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Universal Pansharpening Model The use of the normalized difference water index (ndwi) in the delineation of open water features,

Reference 93

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This paper cites Coincident detection of crop water stress, nitrogen status and canopy density using ground based multispectral data,.

Universal Pansharpening Model Coincident detection of crop water stress, nitrogen status and canopy density using ground based multispectral data,

Reference 94

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Universal Pansharpening Model Use of normalized difference built-up index in automatically mapping urban areas from tm imagery,

Reference 95

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