Paper Citation Record · LEDGER

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing

As of 21 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 1 inbound Pith citation observation for arXiv:2412.07195.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.07195 v2

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:09:09.584447Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T18:32:34.439713Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-13T18:33:06.517324Z

Reference resolution

59 of 59 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 483c41d6-944b-4b5f-85ae-29d7a2fd7187 · outbound

This paper cites Unetformer: A unet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Unetformer: A unet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery,

Reference 1

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Observation 2b4475fb-9075-42fc-9971-3be076e4826a · outbound

This paper cites Learning enriched features for fast image restoration and enhancement,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Learning enriched features for fast image restoration and enhancement,

Reference 2

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Observation dede58d5-c168-435d-a5da-27c348c6e657 · outbound

This paper cites Focal network for image restoration,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Focal network for image restoration,

Reference 3

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Observation ffa88f01-c3f1-49b7-9ea4-8acb12128c52 · outbound

This paper cites Rethinking coarse-to-fine approach in single image deblurring,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Rethinking coarse-to-fine approach in single image deblurring,

Reference 4

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Observation c2a8fc87-e5fe-4a98-80b4-79588144a54e · outbound

This paper cites Selective frequency network for image restoration,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Selective frequency network for image restoration,

Reference 5

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Observation cbca153e-9b08-4f2e-a912-008e7c3431c5 · outbound

This paper cites Nest-dgil: Nesterov- optimized deep geometric incremental learning for cs image reconstruc- tion,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Nest-dgil: Nesterov- optimized deep geometric incremental learning for cs image reconstruc- tion,

Reference 6

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Observation 8de5e0d2-a496-4408-9c33-a233fac1d408 · outbound

This paper cites Real-world remote sensing image super-resolution via a practical degradation model and a kernel-aware network,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Real-world remote sensing image super-resolution via a practical degradation model and a kernel-aware network,

Reference 8

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Observation a9758387-6882-4978-ad1f-cdac27059611 · outbound

This paper cites Real-world image super-resolution as multi-task learning,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Real-world image super-resolution as multi-task learning,

Reference 9

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Observation 0ce49c05-659e-4794-8ef2-35380b0d6e56 · outbound

This paper cites Revitalizing convolutional network for image restoration,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Revitalizing convolutional network for image restoration,

Reference 10

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Observation ca3de67f-b267-4ab9-bb01-aad499c1b935 · outbound

This paper cites Representing noisy image without denoising,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Representing noisy image without denoising,

Reference 11

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Observation 8e534af6-3442-4c2e-823b-6af152e57f49 · outbound

This paper cites Simple baselines for image restoration,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Simple baselines for image restoration,

Reference 12

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Observation e03004d0-8a7a-458f-84a0-0d8b96d316f8 · outbound

This paper cites Image restoration via frequency selection,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Image restoration via frequency selection,

Reference 13

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Observation 2adcde75-b89e-4c42-83ae-70f8e452c186 · outbound

This paper cites Image super- resolution using very deep residual channel attention networks,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Image super- resolution using very deep residual channel attention networks,

Reference 14

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Observation 47e9ec86-208a-4208-93fc-2cb819e41b76 · outbound

This paper cites Fast ultra high-definition video deblurring via multi-scale separable network,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Fast ultra high-definition video deblurring via multi-scale separable network,

Reference 15

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Observation 563ecc3b-4350-4447-a669-163440fa28ce · outbound

This paper cites Learning enriched features for real image restoration and enhancement,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Learning enriched features for real image restoration and enhancement,

Reference 16

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Observation 468952e2-7b3e-424c-89c3-2aae5a06e53c · outbound

This paper cites Swinir: Image restoration using swin transformer,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Swinir: Image restoration using swin transformer,

Reference 17

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Observation 20872619-736a-4d58-bbd0-1920bb056063 · outbound

This paper cites an unresolved cited work.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Unresolved cited work

Reference 18

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Observation fdbe9033-2677-4f27-8c04-6c76cf168c81 · outbound

This paper cites Gaussian kernel mixture network for single image defocus deblurring,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Gaussian kernel mixture network for single image defocus deblurring,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:09:10.389912Z

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Observation 29b37fd1-5062-4770-a522-c9613e4d403a · outbound

This paper cites Context aware edge-enhanced gan for remote sensing image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Context aware edge-enhanced gan for remote sensing image super-resolution,

Reference 20

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Observation 2aaba93a-579b-4203-b1af-af5f3a23a1b4 · outbound

This paper cites Image super-resolution using deep convolutional networks,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Image super-resolution using deep convolutional networks,

Reference 21

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Observation 13f1a885-2f38-4138-9539-326ffd03ca6d · outbound

This paper cites Esrgan: Enhanced super-resolution generative adversar- ial networks,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Esrgan: Enhanced super-resolution generative adversar- ial networks,

Reference 22

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Observation b105ec1b-72bc-4adb-94aa-1b6951c17bf8 · outbound

This paper cites Residual dense network for image restoration,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Residual dense network for image restoration,

Reference 23

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Observation e97548cf-dcab-4c17-be80-da3dde205b06 · outbound

This paper cites Residual dense net- work for image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Residual dense net- work for image super-resolution,

Reference 24

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Observation 223e9e1b-ad75-469b-9dc2-1e4df9f88903 · outbound

This paper cites Second-order attention network for single image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Second-order attention network for single image super-resolution,

Reference 25

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Observation 8f6df7c0-853c-44d1-b4bc-bb59405b1ee5 · outbound

This paper cites Restormer: Efficient transformer for high-resolution image restoration,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Restormer: Efficient transformer for high-resolution image restoration,

Reference 26

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Observation 19b9c719-e544-4e3e-80ed-7b9cb0a026ec · outbound

This paper cites Dual aggregation transformer for image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Dual aggregation transformer for image super-resolution,

Reference 27

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Observation 4718871d-33ff-405b-ad85-c14c1313691c · outbound

This paper cites Image super-resolution with non-local sparse attention,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Image super-resolution with non-local sparse attention,

Reference 28

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Observation 14ad3c80-d0e6-4456-ab01-4f383543e5c5 · outbound

This paper cites Remote sensing image super- resolution via mixed high-order attention network,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Remote sensing image super- resolution via mixed high-order attention network,

Reference 29

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Observation 0334b953-c113-4bfc-aa90-4fb832abfa97 · outbound

This paper cites Super-resolution for remote sensing images via local–global combined network,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Super-resolution for remote sensing images via local–global combined network,

Reference 30

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Observation 83094963-37a6-4c43-b353-a1e2a4080304 · outbound

This paper cites Ttst: A top-k token selective transformer for remote sensing image super- resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Ttst: A top-k token selective transformer for remote sensing image super- resolution,

Reference 31

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Observation 4b55347a-6d3b-41ee-a752-87e270fbbc50 · outbound

This paper cites Glf-cr: Sar-enhanced cloud removal with global–local fusion,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Glf-cr: Sar-enhanced cloud removal with global–local fusion,

Reference 32

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Observation a4760702-391d-427a-83f0-77f4392a316f · outbound

This paper cites Transformer-based multistage enhancement for remote sensing image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Transformer-based multistage enhancement for remote sensing image super-resolution,

Reference 33

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Observation 7bbe3994-b462-4d6b-aafc-e75515c157d3 · outbound

This paper cites Hybrid attention- based u-shaped network for remote sensing image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Hybrid attention- based u-shaped network for remote sensing image super-resolution,

Reference 34

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Observation 72b572af-2bc0-4d85-8bee-578854f16092 · outbound

This paper cites Designing a practical degradation model for deep blind image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Designing a practical degradation model for deep blind image super-resolution,

Reference 35

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Observation 92c6338b-712a-4910-bbe4-5dc6bb3780ab · outbound

This paper cites Real-esrgan: Training real- world blind super-resolution with pure synthetic data,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Real-esrgan: Training real- world blind super-resolution with pure synthetic data,

Reference 36

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Observation 1e0f921c-238d-4c68-a7c7-cb6cc34eaedf · outbound

This paper cites Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Towards Effective Multiple-in-One Image Restoration: A Sequential and Prompt Learning Strategy

Reference 37

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Observation 5430b649-e072-49ac-9cf9-62e6542626fb · outbound

This paper cites Promptir: Prompting for all-in-one image restoration,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Promptir: Prompting for all-in-one image restoration,

Reference 38

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Observation a6e5d5a5-1f42-496d-aec8-4f4286b4690c · outbound

This paper cites Unfolding the alternating optimization for blind super resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Unfolding the alternating optimization for blind super resolution,

Reference 39

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Observation 69755c91-3cba-4708-8fdf-a00589fddeff · outbound

This paper cites Blind super-resolution with iterative kernel correction,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Blind super-resolution with iterative kernel correction,

Reference 40

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Observation ac064be7-4cbf-45cd-a023-fb920cdf450b · outbound

This paper cites Deep generalized unfolding networks for image restoration,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Deep generalized unfolding networks for image restoration,

Reference 41

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Observation a0d7ce30-f3f7-41cb-9303-980ded2c6ff6 · outbound

This paper cites Deep unfolding network for image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Deep unfolding network for image super-resolution,

Reference 42

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Observation 743e23c4-057a-40a6-b75c-fa504c10cdd1 · outbound

This paper cites Deep geometric distillation network for compressive sensing mri,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Deep geometric distillation network for compressive sensing mri,

Reference 43

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Observation 8cb9219f-28ee-4f6b-819b-d9cf8feb131e · outbound

This paper cites Mvms-rcn: A dual- domain unified ct reconstruction with multi-sparse-view and multi-scale refinement-correction,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Mvms-rcn: A dual- domain unified ct reconstruction with multi-sparse-view and multi-scale refinement-correction,

Reference 44

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Observation e8735d6e-2e1c-4e62-8901-5a59c3fbf313 · outbound

This paper cites Intriguing findings of frequency selection for image deblurring,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Intriguing findings of frequency selection for image deblurring,

Reference 45

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Observation ea19145f-6b4e-4535-a41e-610d41d797a7 · outbound

This paper cites Neumann network with recursive kernels for single image defocus deblurring,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Neumann network with recursive kernels for single image defocus deblurring,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:09:09.993110Z

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Observation 4fbe85bd-e645-49a7-97c5-d79318918991 · outbound

This paper cites Satellite image classification via two-layer sparse coding with biased image representation,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Satellite image classification via two-layer sparse coding with biased image representation,

Reference 47

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Observation 5e33827b-82c6-43ea-9b0f-621d070d4497 · outbound

This paper cites Aid: A benchmark data set for performance evaluation of aerial scene classification,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Aid: A benchmark data set for performance evaluation of aerial scene classification,

Reference 48

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Observation c73dd091-0e58-4139-9743-e62d7bab2c76 · outbound

This paper cites Dota: A large-scale dataset for object detection in aerial images,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Dota: A large-scale dataset for object detection in aerial images,

Reference 49

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Observation 4701ce89-a33d-425c-9c4b-7e26e0c7e18b · outbound

This paper cites Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Fully convolutional networks for multisource building extraction from an open aerial and satellite imagery data set,

Reference 50

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Observation f66ef4bf-4c37-496e-a6aa-79da287d44cb · outbound

This paper cites Bag-of-visual-words and spatial extensions for land-use classification,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Bag-of-visual-words and spatial extensions for land-use classification,

Reference 51

Resolution: metadata mismatch; raw_fallback, observed 2026-08-11T19:09:09.753072Z

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Observation 05db5099-4dfc-4029-80c1-8b09663f6582 · outbound

This paper cites Deep learning based feature selection for remote sensing scene classification,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Deep learning based feature selection for remote sensing scene classification,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:09:09.899908Z

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Observation 3d685c21-62c8-41ca-8ce0-43aa1ba0b57c · outbound

This paper cites Image quality assessment: from error visibility to structural similarity,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Image quality assessment: from error visibility to structural similarity,

Reference 53

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Observation 4b856182-3315-45c5-9f34-2e29f57d7d3b · outbound

This paper cites Remote sensing image scene classifi- cation: Benchmark and state of the art,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Remote sensing image scene classifi- cation: Benchmark and state of the art,

Reference 54

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Observation 5cc5f7c4-ef3a-4f82-b0c1-7779203ad35b · outbound

This paper cites Deep back-projection networks for super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Deep back-projection networks for super-resolution,

Reference 55

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This paper cites No-reference image quality assessment in the spatial domain,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing No-reference image quality assessment in the spatial domain,

Reference 56

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This paper cites Recursive general- ization transformer for image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Recursive general- ization transformer for image super-resolution,

Reference 57

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This paper cites Cross aggregation transformer for image restoration,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Cross aggregation transformer for image restoration,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:09:09.826815Z

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This paper cites Contextual transformation network for lightweight remote-sensing image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Contextual transformation network for lightweight remote-sensing image super-resolution,

Reference 60

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Observation f39679f3-dd32-4793-ab7f-59ab45837b3c · outbound

This paper cites Hybrid-scale self-similarity exploitation for remote sensing image super-resolution,.

A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing Hybrid-scale self-similarity exploitation for remote sensing image super-resolution,

Reference 61

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Pith citing papers

Observation 497780a3-cbdd-4d8e-a944-8624a6d3a5cd · inbound

Task-Guided Prompting for Unified Remote Sensing Image Restoration cites this paper.

Task-Guided Prompting for Unified Remote Sensing Image Restoration A Progressive Image Restoration Network for High-order Degradation Imaging in Remote Sensing

Reference 27

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