Paper Citation Record · LEDGER

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery

As of 11 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2501.11923.

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

pith.paper-citation-record.v1
2501.11923 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:47:41.290523Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

18 of 18 outbound references displayed

verified exact1
verified fuzzy11
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1e369234-b677-46cb-8ea5-bb021b30b858 · outbound

This paper cites Satellite imaging reveals increased proportion of population exposed to floods,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Satellite imaging reveals increased proportion of population exposed to floods,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.771762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4b052444-5c42-4292-a991-a1a716e004eb · outbound

This paper cites The impact of climate -change-related disasters on africa’s economic growth, agriculture, and conflicts: Can humanitarian aid and food assistance offset the damage?,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery The impact of climate -change-related disasters on africa’s economic growth, agriculture, and conflicts: Can humanitarian aid and food assistance offset the damage?,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.756683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c3cad747-5f86-4301-abf6-ddbfd11c5cb7 · outbound

This paper cites Predicting inflow rate of the Soyang river dam using deep learning techniques,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Predicting inflow rate of the Soyang river dam using deep learning techniques,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.741461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation da6296b9-1d4d-4c67-8aa6-242eb797d3fd · outbound

This paper cites an unresolved cited work.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-10T17:47:41.725902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 54390be8-1620-4bbb-bbe1-8213697dbd47 · outbound

This paper cites Deep attentive fusion network for flood detection on uni -temporal Sentinel -1 data,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Deep attentive fusion network for flood detection on uni -temporal Sentinel -1 data,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.709913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 47b3419f-cf67-4ab3-a6cb-0eafd67ddc4f · outbound

This paper cites A deep learning technique -based data -driven model for accurate and rapid flood prediction,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery A deep learning technique -based data -driven model for accurate and rapid flood prediction,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.692011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2a1c1e6d-cf7b-460e-9a01-1fa1ade083be · outbound

This paper cites Boundary-Aware Segmentation Network for Mobile and Web Applications.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Boundary-Aware Segmentation Network for Mobile and Web Applications

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T17:47:41.241145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64ed53f7-b582-4fd4-b16e-a3c5d3f2e5a4 · outbound

This paper cites From local to regional compound flood mapping with deep learning and data fusion techniques,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery From local to regional compound flood mapping with deep learning and data fusion techniques,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.673440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7441456a-6a41-475a-8ae5-2ae65cfb7c4a · outbound

This paper cites Attention U-Net: Learning Where to Look for the Pancreas.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Attention U-Net: Learning Where to Look for the Pancreas

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T17:47:41.250899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37250fb0-0a80-4a2c-bfbf-bce7c2213b6c · outbound

This paper cites Design and Experiment of Online Detection System for Water Content of Fresh Tea Leaves after Harvesting Based on Near Infra -Red Spectroscopy,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Design and Experiment of Online Detection System for Water Content of Fresh Tea Leaves after Harvesting Based on Near Infra -Red Spectroscopy,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.656890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 60b89d9e-73c5-4aad-9e8c-79fc70884819 · outbound

This paper cites Applications in Remote Sensing to Forest Ecology and Management,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Applications in Remote Sensing to Forest Ecology and Management,

Reference 11

Resolution: verified exact; doi, observed 2026-08-10T17:47:41.328414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation da182000-449c-498c-8401-664acbdace27 · outbound

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

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery U -net: Convolutional networks for biomedical image segmentation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.640163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 34f68cf1-1f22-4217-a948-286d208c2ca7 · outbound

This paper cites Sen1Floods11: A georeferenced dataset to train and test deep learning flood algorithms for sentinel -1,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Sen1Floods11: A georeferenced dataset to train and test deep learning flood algorithms for sentinel -1,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.623414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 842d7951-2cf7-4779-b641-43028ea2b971 · outbound

This paper cites Pyramid scene parsing network,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Pyramid scene parsing network,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T17:47:41.272962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d75f0683-3f52-42c3-b571-0b293adc6373 · outbound

This paper cites Linknet: Exploiting encoder representations for efficient semantic segmentation,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Linknet: Exploiting encoder representations for efficient semantic segmentation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.597170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f85623ba-66e3-4e08-ab08-7c1a01d34e98 · outbound

This paper cites Multiattention network for semantic segmentation of fine -resolution remote sensing images,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Multiattention network for semantic segmentation of fine -resolution remote sensing images,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:47:41.580854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2cd4dec3-2bf2-41b8-a971-d460715b48e1 · outbound

This paper cites Pyramid Attention Network for Semantic Segmentation.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery Pyramid Attention Network for Semantic Segmentation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T17:47:41.285448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7239ec5-c8df-4421-935c-aff4cbf0a9f1 · outbound

This paper cites ConvNeXt V2: Co -designing and Scaling ConvNets with Masked Autoencoders,.

Progressive Cross Attention Network for Flood Segmentation using Multispectral Satellite Imagery ConvNeXt V2: Co -designing and Scaling ConvNets with Masked Autoencoders,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T17:47:41.290523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.