Paper Citation Record · LEDGER

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective

As of 17 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2509.01898.

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

pith.paper-citation-record.v1
2509.01898 v1

Coverage vector

measured 31 of 31 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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

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Reference resolution

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External citation measurements

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Outbound references

Observation 0446382f-b632-4942-a800-8b20e237441e · outbound

This paper cites Denoising diffusion probabilistic models,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Denoising diffusion probabilistic models,

Reference 1

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Observation 77f0bc66-6b67-4783-8220-b1eda965b925 · outbound

This paper cites Improved denoising diffusion probabilis- tic models,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Improved denoising diffusion probabilis- tic models,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:05.631216Z

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Observation 92424d88-0558-4ea9-a89e-2a1f7a8bc93e · outbound

This paper cites Diffusion models beat gans on image synthesis,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Diffusion models beat gans on image synthesis,

Reference 3

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Observation 6eb8a858-1462-4e9b-a331-5b620232670b · outbound

This paper cites Repaint: Inpainting using denoising diffusion probabilistic models,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Repaint: Inpainting using denoising diffusion probabilistic models,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:05.374157Z

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Observation 4b8f46c4-1229-419f-872d-29057882acd8 · outbound

This paper cites Exploiting diffusion prior for real-world image super-resolution,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Exploiting diffusion prior for real-world image super-resolution,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:05.108086Z

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Observation e2eb7405-b28c-4292-bd82-c2d21e568339 · outbound

This paper cites Diffbir: Toward blind image restoration with generative diffusion prior,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Diffbir: Toward blind image restoration with generative diffusion prior,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:04.805982Z

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Observation 8697c3c0-5947-4073-9835-c3e93dea6979 · outbound

This paper cites Tinyfl hkd: Enhancing edge ai federated learning with hierarchical knowledge distillation framework,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Tinyfl hkd: Enhancing edge ai federated learning with hierarchical knowledge distillation framework,

Reference 8

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Observation 0516bbda-4c4f-433b-ab51-58c5d32f3aaf · outbound

This paper cites Infrared detectors: an overview,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Infrared detectors: an overview,

Reference 9

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Observation 3f26a468-8910-44a1-94f0-066a7782653c · outbound

This paper cites Comparison of infrared and visible imagery for object tracking: Toward trackers with superior ir performance,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Comparison of infrared and visible imagery for object tracking: Toward trackers with superior ir performance,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:03.782970Z

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Observation 1afdfddf-bd24-42e9-b4bc-638e8ebe1f9c · outbound

This paper cites DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models

Reference 11

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Observation 66213365-3933-4224-bca8-6fdf3d4b6c1d · outbound

This paper cites Super- resolution reconstruction of infrared images based on a convolutional neural network with skip connections,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Super- resolution reconstruction of infrared images based on a convolutional neural network with skip connections,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:03.564951Z

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Observation 22e9e50d-ac8a-4385-8bbe-5f7d5cfbc05e · outbound

This paper cites Infrared image super-resolution via heterogeneous convolutional wgan,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Infrared image super-resolution via heterogeneous convolutional wgan,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:03.379375Z

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Observation a8678051-c86b-4156-92c0-1e369e6fb6e0 · outbound

This paper cites Swinibsr: Towards real- world infrared image super-resolution,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Swinibsr: Towards real- world infrared image super-resolution,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:03.156563Z

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Observation e0ea163c-22d8-428e-8217-3a8061cc53ce · outbound

This paper cites Infrared thermal imaging super-resolution via multiscale spatio-temporal feature fusion network,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Infrared thermal imaging super-resolution via multiscale spatio-temporal feature fusion network,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:04.534565Z

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Observation b97a88d6-f206-479f-9470-faa085cd158c · outbound

This paper cites Swinipisr: A super-resolution method for infrared polarization imaging sensors via swin transformer,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Swinipisr: A super-resolution method for infrared polarization imaging sensors via swin transformer,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:02.901171Z

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Observation f9406f5a-3890-4651-9d46-438c54bed825 · outbound

This paper cites Taylor-guided iterative gradient projection neural network for coal-dust scanning electron microscopy super resolution,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Taylor-guided iterative gradient projection neural network for coal-dust scanning electron microscopy super resolution,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:02.681493Z

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Observation 3aecae46-ee5c-41c1-81b7-4d03c15a564e · outbound

This paper cites Improving the spatial resolution of small satellites by implementing a super-resolution algo- rithm based on the optical imaging sensor’s rotation approach,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Improving the spatial resolution of small satellites by implementing a super-resolution algo- rithm based on the optical imaging sensor’s rotation approach,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:02.460447Z

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Observation 6f9df62f-12a0-4d21-b2c6-cea3bb99535b · outbound

This paper cites Incorporating degradation estimation in light field spatial super-resolution,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Incorporating degradation estimation in light field spatial super-resolution,

Reference 19

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Observation ec8ca2eb-fa26-43b3-8769-eacd53f8747e · outbound

This paper cites Event- adapted video super-resolution,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Event- adapted video super-resolution,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:02.062260Z

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Observation 9f84bc77-8069-47b5-8d5b-339a5408df7a · outbound

This paper cites Event-based video super-resolution via state space models,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Event-based video super-resolution via state space models,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:01.901559Z

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Observation ea0d3237-d55f-4da0-9539-ee7c0c1ff527 · outbound

This paper cites Deep gate information bottleneck-based prediction model for complex disease-related micro- ribonucleic acids via heterogeneous biological networks,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Deep gate information bottleneck-based prediction model for complex disease-related micro- ribonucleic acids via heterogeneous biological networks,

Reference 22

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Observation 1f8bd78e-e35a-4785-93a5-372f2524869a · outbound

This paper cites Learning spatiotemporal embedding with gated convolutional recurrent networks for translation initiation site prediction,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Learning spatiotemporal embedding with gated convolutional recurrent networks for translation initiation site prediction,

Reference 23

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Observation 81c084c9-0e76-4aae-84e6-50c3d1849b66 · outbound

This paper cites Denoising Diffusion Implicit Models.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Denoising Diffusion Implicit Models

Reference 24

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Observation 0e2b87b7-50d1-4c01-af4d-b8e7d2b23c28 · outbound

This paper cites Image super-resolution via iterative refinement,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Image super-resolution via iterative refinement,

Reference 25

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Observation 2ce19973-0d24-4ba6-8fe3-4162e17f714c · outbound

This paper cites Auto-encoding variational bayes,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Auto-encoding variational bayes,

Reference 26

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Observation b2709d43-438b-4af7-98f7-b1f2db19362b · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective U-net: Convolutional networks for biomedical image segmentation,

Reference 27

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Observation b055cb44-8ada-4267-843c-3a6e47a397f6 · outbound

This paper cites High- resolution image synthesis with latent diffusion models,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective High- resolution image synthesis with latent diffusion models,

Reference 28

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Observation e8911b44-5c15-43e6-9a13-cdbdb5b6a953 · outbound

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

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Restormer: Efficient transformer for high-resolution image restoration,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:01.291615Z

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Observation c33512e7-c0f5-45b1-9335-19d732c4c46e · outbound

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

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Real-esrgan: Training real- world blind super-resolution with pure synthetic data,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:01.170139Z

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Observation 90ef5305-89a7-4c0c-9734-fa2ee0390790 · outbound

This paper cites Lirsrn: A lightweight infrared image super-resolution network,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Lirsrn: A lightweight infrared image super-resolution network,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:00.991666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d87ead82-eccd-40f6-93b5-e63d09f71211 · outbound

This paper cites Resshift: Efficient diffusion model for image super-resolution by residual shifting,.

DroneSR: Rethinking Few-shot Thermal Image Super-Resolution from Drone-based Perspective Resshift: Efficient diffusion model for image super-resolution by residual shifting,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T12:14:00.828247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

No inbound Pith citation observations are available.