Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:49:09.194282Z
Paper Citation Record · LEDGER
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene
As of 18 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2506.15890.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
33 of 33 outbound references displayed
- verified exact3
- verified fuzzy26
- unresolved4
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 10eff089-0ced-462a-afe1-eb58b6062cc7 · outbound
This paper cites 2024 atlantic hurricane season,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene 2024 atlantic hurricane season,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:16.926591Z
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 fb205a90-5b3f-4069-b53c-f91f1911dbdf · outbound
This paper cites Microsoft us building footprints,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Microsoft us building footprints,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:16.624963Z
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 d55b77d5-d7e4-4fb8-8f9c-9e8a4deff732 · outbound
This paper cites Use of small unmanned aerial systems for tactical response during kilauea volcano lower east rift zone event,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Use of small unmanned aerial systems for tactical response during kilauea volcano lower east rift zone event,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:16.390678Z
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 80637e3e-e4ea-443c-92c9-bd80b3db9870 · outbound
This paper cites Big data and disaster management: a systematic review and agenda for future research,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Big data and disaster management: a systematic review and agenda for future research,
Reference 4
- Resolution
- verified exact
- doi, observed 2026-08-06T23:49:09.399695Z
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 44a02e38-32af-43c4-91ba-8a7c87696b30 · outbound
This paper cites Integrating machine learning and remote sensing in disaster management: A decadal review of post-disaster building damage assessment,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Integrating machine learning and remote sensing in disaster management: A decadal review of post-disaster building damage assessment,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:16.199622Z
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 443bfeb9-36db-4cdd-9c9e-484b08688304 · outbound
This paper cites Disaster and pandemic management using machine learning: a survey,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Disaster and pandemic management using machine learning: a survey,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:15.981350Z
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 6a7e2d22-02de-42c5-846d-399fb9755d18 · outbound
This paper cites Dorianet: A visual dataset from hurricane dorian for post-disaster building damage assessment,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Dorianet: A visual dataset from hurricane dorian for post-disaster building damage assessment,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:15.759269Z
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 680a69a2-3530-4386-8533-e5e8363a9013 · outbound
This paper cites an unresolved cited work.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T23:49:15.438205Z
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 578a063d-66e2-4da7-868b-240f9b0f4adc · outbound
This paper cites Applications of drone in disaster management: A scoping review,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Applications of drone in disaster management: A scoping review,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:15.184174Z
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 864578b8-46b7-4107-a8c7-ae4efe413331 · outbound
This paper cites Quantitative data analysis: Crasar small unmanned aerial systems at hurricane harvey,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Quantitative data analysis: Crasar small unmanned aerial systems at hurricane harvey,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:14.928311Z
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 847ce691-28e7-49fc-b73b-acc751093e55 · outbound
This paper cites Quantitative data analysis: Small unmanned aerial systems at hurricane michael,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Quantitative data analysis: Small unmanned aerial systems at hurricane michael,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:14.676384Z
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 64bc6a26-2e4c-447d-99a9-91f4cc49ccfe · outbound
This paper cites Computer vision-based post-disaster needs assessment from low altitude aerial imagery,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Computer vision-based post-disaster needs assessment from low altitude aerial imagery,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:14.419884Z
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 5ea6a9a5-79e7-453e-802b-0019399f2840 · outbound
This paper cites xBD: A Dataset for Assessing Building Damage from Satellite Imagery.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene xBD: A Dataset for Assessing Building Damage from Satellite Imagery
Reference 13
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6f2fa5c1-d308-4ec0-a645-9b8ec273b43b · outbound
This paper cites Drones for flood monitoring, mapping and detection: A bibliometric review,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Drones for flood monitoring, mapping and detection: A bibliometric review,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:14.204140Z
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 8592f1b9-207c-4b2a-93c0-0e98cfb6fa31 · outbound
This paper cites Uav-based structural damage mapping: A review,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Uav-based structural damage mapping: A review,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:13.946095Z
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 fc8d4e19-172f-45b1-84f0-67d4bb7ba863 · outbound
This paper cites Advances in ai and drone-based natural disaster management: A survey,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Advances in ai and drone-based natural disaster management: A survey,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:13.762665Z
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 62804650-f5c9-40b6-9986-20527b90363e · outbound
This paper cites Machine learning for emergency management: A survey and future outlook,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Machine learning for emergency management: A survey and future outlook,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:13.523767Z
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 87b17d1a-5d27-4645-960c-287f65c74cc5 · outbound
This paper cites Machine learning in disaster management: recent developments in methods and applications,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Machine learning in disaster management: recent developments in methods and applications,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:13.255809Z
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 0f75a5d2-557c-4347-8f0c-812f351ef3d7 · outbound
This paper cites Data collection tools for post-disaster damage assessment of building and lifeline infrastructure systems,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Data collection tools for post-disaster damage assessment of building and lifeline infrastructure systems,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:12.951704Z
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 29442bde-9cc4-4ad0-97ea-59f6b8f54394 · outbound
This paper cites Effect of label noise in semantic segmentation of high resolution aerial images and height data,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Effect of label noise in semantic segmentation of high resolution aerial images and height data,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:12.645285Z
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 9ffe1f2b-4257-406c-8340-b8dddd547557 · outbound
This paper cites Quantitative data analysis: Crasar small unmanned aerial systems at hurricane ian,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Quantitative data analysis: Crasar small unmanned aerial systems at hurricane ian,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:12.392663Z
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 66da24b5-8178-4089-87ed-8006eff2be03 · outbound
This paper cites Wireless network demands of data products from small uncrewed aerial systems at hur- ricane ian,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Wireless network demands of data products from small uncrewed aerial systems at hur- ricane ian,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:12.095829Z
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 6fdc0bbb-08b0-4b55-8110-aaf7a694a37a · outbound
This paper cites Non-Uniform Spatial Alignment Errors in sUAS Imagery From Wide-Area Disasters.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Non-Uniform Spatial Alignment Errors in sUAS Imagery From Wide-Area Disasters
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T23:49:10.049121Z
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 7257823f-4123-42ad-a3f1-ba429945ff1f · outbound
This paper cites CRASAR-U-DROIDs: A Large Scale Benchmark Dataset for Building Alignment and Damage Assessment in Georectified sUAS Imagery.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene CRASAR-U-DROIDs: A Large Scale Benchmark Dataset for Building Alignment and Damage Assessment in Georectified sUAS Imagery
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:49:08.606854Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b19f6e92-bf4e-4067-a778-a2ef01e3149a · outbound
This paper cites Now you see it, Now you don't: Damage Label Agreement in Drone & Satellite Post-Disaster Imagery.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Now you see it, Now you don't: Damage Label Agreement in Drone & Satellite Post-Disaster Imagery
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T23:49:09.714657Z
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 ba428122-0c6a-423c-aa78-a4978206f3ee · outbound
This paper cites Drones4good: Supporting disaster relief through remote sensing and ai,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Drones4good: Supporting disaster relief through remote sensing and ai,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:11.855987Z
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 402c1bf4-ceb7-4a27-826b-9547b94b7a18 · outbound
This paper cites Crew roles and operational protocols for rotary-wing micro-uavs in close urban environments,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Crew roles and operational protocols for rotary-wing micro-uavs in close urban environments,
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:11.625369Z
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 50020263-5642-4aa2-b68f-50dfd3d414b8 · outbound
This paper cites Cooperative use of unmanned sea surface and micro aerial vehicles at hurricane wilma,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Cooperative use of unmanned sea surface and micro aerial vehicles at hurricane wilma,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:11.386167Z
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 dc0e2754-cdbe-4700-92ca-58ea7f0a9df2 · outbound
This paper cites Robot-assisted bridge inspection after hurricane ike,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Robot-assisted bridge inspection after hurricane ike,
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:11.092243Z
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 463931b7-6f0f-4927-aa7e-3f2570c9bca9 · outbound
This paper cites Attention U-Net: Learning Where to Look for the Pancreas.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Attention U-Net: Learning Where to Look for the Pancreas
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:49:08.984273Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7d53c59-f290-4a70-a04c-9eec0254ef34 · outbound
This paper cites Analysis of interior rubble void spaces at champlain towers south collapse,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Analysis of interior rubble void spaces at champlain towers south collapse,
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:10.828635Z
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 3bfa78b8-f29b-409a-889f-0115290c7e9c · outbound
This paper cites Scale-mae: A scale-aware masked autoencoder for multiscale geospatial repre- sentation learning,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Scale-mae: A scale-aware masked autoencoder for multiscale geospatial repre- sentation learning,
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:10.557307Z
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 6d37dfb6-fb20-4416-aa32-a2424e3ded4e · outbound
This paper cites Correcting rural building annotations in openstreetmap using convolutional neural networks,.
Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene Correcting rural building annotations in openstreetmap using convolutional neural networks,
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:49:10.368721Z
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.