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Paper Citation Record · LEDGER

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies

As of 21 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2504.20203.

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

pith.paper-citation-record.v1
2504.20203 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:36:39.556878Z

measured 29 of 29 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 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

29 of 29 outbound references displayed

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  • verified fuzzy25
  • unresolved4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b5c91f38-d1e9-43ed-96cb-f2bff33b761f · outbound

This paper cites Ritchie and P.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Ritchie and P

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 40999294-fcff-4991-800a-11f870803478 · outbound

This paper cites Arias, N.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Arias, N

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c7b7d56c-3f14-45b5-8eae-2f1543829b02 · outbound

This paper cites Deep convolutional neural network for flood extent mapping using unmanned aeria l vehicles data,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Deep convolutional neural network for flood extent mapping using unmanned aeria l vehicles data,

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 34db0313-75a8-4ad3-9025-ba1657529cf9 · outbound

This paper cites an unresolved cited work.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Unresolved cited work

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c3e2fc43-a169-49f2-983f-2e097b06bd33 · outbound

This paper cites The u se of unmanned aerial vehicles in flood hazard assessment,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies The u se of unmanned aerial vehicles in flood hazard assessment,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 5780c0d2-ab48-4c28-8278-dd66a431dfee · outbound

This paper cites Applica tion of deep learning on uav-based aerial images for flood detection,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Applica tion of deep learning on uav-based aerial images for flood detection,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0d62a93b-5dcf-476a-9166-d19a7d5b25fc · outbound

This paper cites Automated indunati on mapping: comparison of methods,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Automated indunati on mapping: comparison of methods,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c5d767bd-16eb-496e-ad12-e0fee9cf3d07 · outbound

This paper cites A Real-Time Flood Detection System Based on Machine Learning Algorithms with Emphasis on Deep L earning,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies A Real-Time Flood Detection System Based on Machine Learning Algorithms with Emphasis on Deep L earning,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4560164d-4f87-498e-9f68-fd46dcee06f9 · outbound

This paper cites Artifical Intelligence (AI) Appli ed to Unmanned Aerial V ehicles (UA Vs) And its Impact on Humanitarian Action,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Artifical Intelligence (AI) Appli ed to Unmanned Aerial V ehicles (UA Vs) And its Impact on Humanitarian Action,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 159a437d-000a-4243-aae6-1aa1dc495135 · outbound

This paper cites Image segmentation using deep learning: A survey,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Image segmentation using deep learning: A survey,

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f8ea2d38-a4a6-425b-bcfd-3ef95b0c6bfd · outbound

This paper cites Deep learning-based flood detection system using semantic segmentation,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Deep learning-based flood detection system using semantic segmentation,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0a9ff6b0-fb4a-4773-a49a-ebd3a4cdfe13 · outbound

This paper cites The use of the normalized di fference water index (ndwi) in the delineation of open water features,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies The use of the normalized di fference water index (ndwi) in the delineation of open water features,

Reference 12

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raw_fallback, observed 2026-08-16T05:36:39.777530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 805bda80-4f13-42ea-8262-3da76888d3fb · outbound

This paper cites Deep learning methods for flood mapping: A review of existing applications and future research direct ions,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Deep learning methods for flood mapping: A review of existing applications and future research direct ions,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 5948f277-ea16-48fb-bca2-c414a2905b6a · outbound

This paper cites Flood extent mapp ing: an integrated method using deep learning and region growing using UA V optical data,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Flood extent mapp ing: an integrated method using deep learning and region growing using UA V optical data,

Reference 14

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raw_fallback, observed 2026-08-16T05:36:39.755512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b63a98d7-4939-4a1f-8fca-1f37e6a7dc27 · outbound

This paper cites Floodnet: A high resolution aerial imagery dataset for post flood scene under standing,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Floodnet: A high resolution aerial imagery dataset for post flood scene under standing,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a1e8e0e4-37fc-4aa8-ab3d-485ade9d7e3c · outbound

This paper cites Blessemflood21: Advancing flood analysis with a high-resol ution georeferenced dataset for humanitarian aid support,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Blessemflood21: Advancing flood analysis with a high-resol ution georeferenced dataset for humanitarian aid support,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d4ec8f25-c147-4a02-ab69-83a854c2fd3a · outbound

This paper cites Image Data Augmentation for Deep Learning: A Survey.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Image Data Augmentation for Deep Learning: A Survey

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d65f0c57-4244-4f94-a75a-d077383b7ec8 · outbound

This paper cites Evaluating Self and Semi-Supervised Methods for Remote Sensing Segmentation Tasks.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Evaluating Self and Semi-Supervised Methods for Remote Sensing Segmentation Tasks

Reference 18

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no resolver link, observed 2026-08-16T05:36:39.515289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 30030a28-a79b-4902-94ee-b180cf612152 · outbound

This paper cites Selective data au gmentation approach for remote sensing scene clas- sification,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Selective data au gmentation approach for remote sensing scene clas- sification,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 782bd9ac-1ab6-47e2-b638-4a5cd5c56069 · outbound

This paper cites Automatic detection of passable roads after floods in remote sensed and social media data,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Automatic detection of passable roads after floods in remote sensed and social media data,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-16T05:36:39.709863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation fe24d0e7-ad96-4155-bfc1-8892ada4439c · outbound

This paper cites Ha-net: A lake water body ex traction network based on hybrid-scale attention and transfer learning,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Ha-net: A lake water body ex traction network based on hybrid-scale attention and transfer learning,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c114547f-3178-4f05-81c2-e64a70b6e572 · outbound

This paper cites Deep learning semantic segmentation for water level estimation using surveillance camera,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Deep learning semantic segmentation for water level estimation using surveillance camera,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 93a50bff-72d0-4a48-82e8-6bcf60d6eb34 · outbound

This paper cites Urban flood mappin g with residual patch similarity learning,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Urban flood mappin g with residual patch similarity learning,

Reference 23

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raw_fallback, observed 2026-08-16T05:36:39.676972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 567e250e-b443-49ce-b638-e1a23a7c3d7f · outbound

This paper cites an unresolved cited work.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Unresolved cited work

Reference 24

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unresolved
raw_fallback, observed 2026-08-16T05:36:39.665277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 269e6ce0-5ba3-466a-8a8b-45c57694d1c5 · outbound

This paper cites Unet ++: A nested u-net architecture for medical image segmentation,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Unet ++: A nested u-net architecture for medical image segmentation,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-16T05:36:39.653950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation e5e182fc-93f1-4505-81da-9bfae56f18e1 · outbound

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

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Encoder-decoder with atrous separable convolution for semantic image segmentation,

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-16T05:36:39.643111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f1f58079-e163-442e-9c78-4e4941d95103 · outbound

This paper cites Albumentations: fast and flexible image augmentations,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Albumentations: fast and flexible image augmentations,

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-16T05:36:39.631579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a22cc797-ac98-4142-b425-d0f58c3c5360 · outbound

This paper cites Data augmentation in c lassification and segmentation: A survey and new strategies,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Data augmentation in c lassification and segmentation: A survey and new strategies,

Reference 28

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raw_fallback, observed 2026-08-16T05:36:39.620037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4473b3b9-d2ea-417f-a4c1-3894c8aae716 · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Remote Sensing Imagery for Flood Detection: Exploration of Augmentation Strategies Imagenet: A large-scale hierarchical image database,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-16T05:36:39.608614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Pith citing papers

No inbound Pith citation observations are available.