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Paper Citation Record · LEDGER

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework

As of 5 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2604.13994.

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

pith.paper-citation-record.v1
2604.13994 v1

Coverage vector

measured 43 of 43 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-05-10T13:22:55.061941Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation 296c2830-7d34-4881-bcbb-86e808956368 · outbound

This paper cites Dream- clear: High-capacity real-world image restoration with privacy-safe dataset curation.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Dream- clear: High-capacity real-world image restoration with privacy-safe dataset curation

Reference 1

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Observation 0eda26b8-0f56-41c9-9dc2-1903009e1d86 · outbound

This paper cites Blind super-resolution kernel estimation using an internal-gan.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Blind super-resolution kernel estimation using an internal-gan

Reference 2

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Observation cff2a750-6541-43fd-bbd9-fe5df3b2b235 · outbound

This paper cites Pixart-α: Fast training of diffusion trans- former for photorealistic text-to-image synthesis.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Pixart-α: Fast training of diffusion trans- former for photorealistic text-to-image synthesis

Reference 3

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Observation 08eea566-910d-4a32-b777-9f9f94c3e73a · outbound

This paper cites FaithD- iff: Unleashing diffusion priors for faithful image super- resolution.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework FaithD- iff: Unleashing diffusion priors for faithful image super- resolution

Reference 4

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Observation 2d7da21f-2927-4f9a-812e-330f96ff5c79 · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Encoder-decoder with atrous separable convolution for semantic image segmentation

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 402229cd-fc47-4fb3-8666-a6bbac011705 · outbound

This paper cites an unresolved cited work.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Unresolved cited work

Reference 6

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Observation 5c200a6a-4ffd-4529-9616-d81a47d837f0 · outbound

This paper cites MMSegmentation: Openmmlab semantic segmentation toolbox and benchmark.https : / / github.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework MMSegmentation: Openmmlab semantic segmentation toolbox and benchmark.https : / / github

Reference 7

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Observation 609fe8c5-d6dc-43ef-b6b4-f59e1d42ea7f · outbound

This paper cites Image quality assessment: Unifying structure and texture similarity.IEEE Transactions on Pattern Analysis and Ma- chine Intelligence.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Image quality assessment: Unifying structure and texture similarity.IEEE Transactions on Pattern Analysis and Ma- chine Intelligence

Reference 8

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Observation 8043089c-91e0-4fbe-a151-ddb1554d883d · outbound

This paper cites Learning a deep convolutional network for image super-resolution.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Learning a deep convolutional network for image super-resolution

Reference 9

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Observation 4b70f3c2-842f-4733-ab49-26f92fbd85b2 · outbound

This paper cites Auto-encoding varia- tional bayes.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Auto-encoding varia- tional bayes

Reference 10

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Source-reported events for the cited work

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Observation 32fed89f-f393-4f46-bd83-2869ad15eabc · outbound

This paper cites Photo- realistic single image super-resolution using a generative ad- versarial network.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Photo- realistic single image super-resolution using a generative ad- versarial network

Reference 11

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Source-reported events for the cited work

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Observation 660fd093-1b89-4f18-9f42-e36ab102b6ce · outbound

This paper cites Srdiff: Single image super-resolution with diffusion probabilistic models.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Srdiff: Single image super-resolution with diffusion probabilistic models

Reference 12

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Observation d9600cbc-61dd-4a07-bf14-790f3e692d36 · outbound

This paper cites SwinIR: Image restoration using swin transformer.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework SwinIR: Image restoration using swin transformer

Reference 13

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Source-reported events for the cited work

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Observation 3b582aba-250e-4e41-8e5a-65f25399259c · outbound

This paper cites Enhanced deep residual networks for single image super-resolution.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Enhanced deep residual networks for single image super-resolution

Reference 14

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Source-reported events for the cited work

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Observation 6e7cd0fc-6dda-484c-bf23-18cc63bc5999 · outbound

This paper cites Super-resolution-based change detection network with stacked attention module for images with different resolutions.IEEE Transactions on Geoscience and Remote Sensing.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Super-resolution-based change detection network with stacked attention module for images with different resolutions.IEEE Transactions on Geoscience and Remote Sensing

Reference 15

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Source-reported events for the cited work

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Observation b0cccb3c-b725-4ed0-b540-eeae1b66dc9a · outbound

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Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Unresolved cited work

Reference 16

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Observation cb7e7b98-8c42-4fe4-86ae-9341fd4e1d5e · outbound

This paper cites RePaint: Inpainting using denoising diffusion probabilistic models.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework RePaint: Inpainting using denoising diffusion probabilistic models

Reference 17

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Observation ca6932eb-7636-463f-a83d-d3380a28228f · outbound

This paper cites No-reference image quality assessment in the spa- tial domain.IEEE Transactions on Image Processing.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework No-reference image quality assessment in the spa- tial domain.IEEE Transactions on Image Processing

Reference 18

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Source-reported events for the cited work

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Observation dc94d164-59c6-4807-9f22-96caee5722f2 · outbound

This paper cites completely blind.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework completely blind

Reference 19

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Observation 68750cb9-6d90-464d-8311-885eba305e32 · outbound

This paper cites ControlNeXt: Powerful and Efficient Control for Image and Video Generation.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework ControlNeXt: Powerful and Efficient Control for Image and Video Generation

Reference 20

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Observation 6e087093-d2a3-40ec-8d0b-0b5172681bc2 · outbound

This paper cites SDXL: Improving latent diffusion mod- els for high-resolution image synthesis.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework SDXL: Improving latent diffusion mod- els for high-resolution image synthesis

Reference 21

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Source-reported events for the cited work

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Observation e6f6c424-1e6d-405a-8cc2-bde3f9192725 · outbound

This paper cites Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network

Reference 22

Resolution
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Source-reported events for the cited work

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Observation 36c17a97-4533-4b8a-b274-2c11c4ce8631 · outbound

This paper cites CoSeR: Bridging image and language for cognitive super-resolution.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework CoSeR: Bridging image and language for cognitive super-resolution

Reference 23

Resolution
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Source-reported events for the cited work

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Observation 05d6211f-8c58-4ef6-9fa2-ede3fa7c3e03 · outbound

This paper cites Semantic guided large scale factor remote sensing image super-resolution with generative dif- fusion prior.ISPRS Journal of Photogrammetry and Remote Sensing.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Semantic guided large scale factor remote sensing image super-resolution with generative dif- fusion prior.ISPRS Journal of Photogrammetry and Remote Sensing

Reference 24

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Source-reported events for the cited work

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Observation ba58c7e7-04d2-4fe8-b04c-9f049d69d9ed · outbound

This paper cites LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation

Reference 25

Resolution
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Source-reported events for the cited work

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Observation 56dc0555-d4ec-41d4-ba19-101bb58aa3b9 · outbound

This paper cites Ex- ploring clip for assessing the look and feel of images.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Ex- ploring clip for assessing the look and feel of images

Reference 26

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation f46513e9-8db8-445a-91ca-801c49d91c6c · outbound

This paper cites Exploiting diffusion prior for real-world image super-resolution.International Journal of Computer Vision.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Exploiting diffusion prior for real-world image super-resolution.International Journal of Computer Vision

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 0ae7707a-0cf0-468d-9e93-9ae256565691 · outbound

This paper cites Recovering realistic texture in image super-resolution by deep spatial feature transform.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Recovering realistic texture in image super-resolution by deep spatial feature transform

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation 679892c8-632f-46f1-a6f0-a694adc3922c · outbound

This paper cites ESRGAN: 9 Enhanced super-resolution generative adversarial networks.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework ESRGAN: 9 Enhanced super-resolution generative adversarial networks

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:deb7a9e3375128685d2a670871e646ec4fc5ba129f21a17330f976e86898f844

Observation b0e7f766-8741-4a11-95b5-0860cd24b03c · outbound

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

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Real-ESRGAN: Training real-world blind super-resolution with pure synthetic data

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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Observation e523e25f-2c36-40c0-a097-28a344df0369 · outbound

This paper cites SinSR: diffusion-based image super- resolution in a single step.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework SinSR: diffusion-based image super- resolution in a single step

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:9bae4794fb3a4ac81df7c2909354cf23647511c678c2d6de42037c7dd2f26c2b

Observation 8c84953c-e134-4c33-a727-d4c2f8093be5 · outbound

This paper cites AID: A benchmark data set for performance evaluation of aerial scene classification.IEEE Transactions on Geoscience and Remote Sensing.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework AID: A benchmark data set for performance evaluation of aerial scene classification.IEEE Transactions on Geoscience and Remote Sensing

Reference 32

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verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.418538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:3c36fa542d1277014bd27eff264f859beebdc9527f3917dac291999b56fbdfd0

Observation fa795cf3-05c2-44a0-b353-03980ba7d22b · outbound

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

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework DOTA: A large-scale dataset for object detection in aerial images

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.444976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:2efdf7e568af94fa1cf3021e666ffa32c91af8a4e709429f334a352926aee7ea

Observation 08d4dcbf-6b03-4d02-b396-9ba708bfbc46 · outbound

This paper cites Pixel-aware stable diffusion for realistic im- age super-resolution and personalized stylization.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Pixel-aware stable diffusion for realistic im- age super-resolution and personalized stylization

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.502600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:5099a395b26f7f6411950abb7ee1691607aa01975884804302bfb2577ba3909f

Observation 50a3db9a-be03-4345-baf7-bf2cfc0460f6 · outbound

This paper cites Scaling up to excellence: Practicing model scaling for photo- realistic image restoration in the wild.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Scaling up to excellence: Practicing model scaling for photo- realistic image restoration in the wild

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.415239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:75078a19447a342fe6ed8a7538cf874370472c754cce25e3fbadff65d87ad762

Observation b6d97f4a-0c76-47ac-a013-32117d31001e · outbound

This paper cites Arbitrary-steps image super-resolution via diffusion inver- sion.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Arbitrary-steps image super-resolution via diffusion inver- sion

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.431202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:ddf872d1b5627159fe6737778422a9ecacaf11f5f25dd3d135e2e166f36942f3

Observation 88de0071-3e35-4936-b4ab-d0802255e958 · outbound

This paper cites Effi- cient diffusion model for image restoration by residual shift- ing.IEEE Transactions on Pattern Analysis and Machine Intelligence.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Effi- cient diffusion model for image restoration by residual shift- ing.IEEE Transactions on Pattern Analysis and Machine Intelligence

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.458003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:4ff1fe79baf6ccd21240d7e4b58834fc752ab490ca622b5d16bc93d9d86d9f7a

Observation c42a5d36-cfe9-4f42-9ed7-b997019a1e42 · outbound

This paper cites SuperYOLO: Super resolution as- sisted object detection in multimodal remote sensing im- agery.IEEE Transactions on Geoscience and Remote Sens- ing.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework SuperYOLO: Super resolution as- sisted object detection in multimodal remote sensing im- agery.IEEE Transactions on Geoscience and Remote Sens- ing

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.506142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:43c2cec07f6081a04a517d130088e7e051c94f92d79e0309ed0f0b1d4904392f

Observation 15481dcd-2bc9-49b5-8d39-accd4633b4bb · outbound

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

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Designing a practical degradation model for deep blind image super-resolution

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.509235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:9ee8fc7a2b6c9e0520a48641266f680ab411897901ba191c0beca566843d07d6

Observation ef887180-0897-4c01-bd01-214b595e5940 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Adding conditional control to text-to-image diffusion models

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.402184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:1374e28c9942f286e95fa6bb95c6cd4926eadec2b68e37ed12ad032b2c6b8a65

Observation 1530ecf9-ca2a-48c0-8b92-13fc76a807ae · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework The unreasonable effectiveness of deep features as a perceptual metric

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.405384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:faebba28dbc4327832cf371a3c1adbd72d0e6f834ef07b2d6a075c6d9785b862

Observation 1c9fe2fd-6076-4e0c-bbbf-cf9ca5fb4bd4 · outbound

This paper cites Dirichlet-derived multiple topic scene classification model for high spatial resolution remote sensing imagery.IEEE Transactions on Geoscience and Remote Sensing.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Dirichlet-derived multiple topic scene classification model for high spatial resolution remote sensing imagery.IEEE Transactions on Geoscience and Remote Sensing

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.408732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:f88cdfdd9cd92615e6a3cc0032ec3afdb5e32d110da05b2e8914d7d22352b102

Observation 8fa7f48b-fe69-4f56-9f44-306256281256 · outbound

This paper cites Feature significance-based multibag-of-visual-words model for re- mote sensing image scene classification.Journal of Applied Remote Sensing.

Remote Sensing Image Super-Resolution for Imbalanced Textures: A Texture-Aware Diffusion Framework Feature significance-based multibag-of-visual-words model for re- mote sensing image scene classification.Journal of Applied Remote Sensing

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-19T00:12:55.470406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T13:22:55.061941Z digest=sha256:a87e20a75478f013396928a784a336022f3b67f71d78f62fa9a9210a20df4076

Pith citing papers

No inbound Pith citation observations are available.