Paper Citation Record · LEDGER

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network

As of 13 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2411.14403.

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

pith.paper-citation-record.v1
2411.14403 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:16:51.234162Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

31 of 31 outbound references displayed

verified exact0
verified fuzzy27
unresolved4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8d1d5500-3edc-4e12-9dbb-62d43e8a5f22 · outbound

This paper cites The Federal Aviation Administration (FAA) Aerospace Forecast Fiscal Years (FY) 2020-2040,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network The Federal Aviation Administration (FAA) Aerospace Forecast Fiscal Years (FY) 2020-2040,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.987450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cc302862-6c0f-4156-bf51-d3bd221f9be9 · outbound

This paper cites Prediction of MUA V flight behavior from active and passive imaging in complex environment,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Prediction of MUA V flight behavior from active and passive imaging in complex environment,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.966156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a4e276f5-7960-4101-a12d-6f2f96e80228 · outbound

This paper cites Optimized landing of drones in the context of congested air traffic and limited vertiports,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Optimized landing of drones in the context of congested air traffic and limited vertiports,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.942468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ae6abaaf-c670-42a4-84c3-ec4a048488cf · outbound

This paper cites UA V path prediction for CD&R to manned aircraft in a confined airspace for cooperative mission,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network UA V path prediction for CD&R to manned aircraft in a confined airspace for cooperative mission,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.922964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation db72f2f9-0537-424a-b148-248a8f6d4689 · outbound

This paper cites Safety Assured Online Guidance With Airborne Separation for Urban Air Mobility Operations in Uncertain Environments,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Safety Assured Online Guidance With Airborne Separation for Urban Air Mobility Operations in Uncertain Environments,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.902383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f8d6a180-78a9-46c5-94e7-8f7000edadd3 · outbound

This paper cites Model-based path prediction for fixed-wing unmanned aircraft using pose estimates,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Model-based path prediction for fixed-wing unmanned aircraft using pose estimates,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.881522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 46e86324-d58c-4c7c-a3e4-acad429e183d · outbound

This paper cites Efficient and robust online trajectory prediction for non-cooperative unmanned aerial vehicles,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Efficient and robust online trajectory prediction for non-cooperative unmanned aerial vehicles,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.859330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 801de5de-1f71-45d2-b1bd-8aa45c343373 · outbound

This paper cites A recurrent neural network approach for aircraft trajectory prediction with weather features from sherlock,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network A recurrent neural network approach for aircraft trajectory prediction with weather features from sherlock,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.839254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3435905c-6dc8-4884-94d6-2593d1200f62 · outbound

This paper cites Aircraft trajectory prediction made easy with predictive analytics,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Aircraft trajectory prediction made easy with predictive analytics,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.813047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0e99117f-4aca-4886-b9e5-d24176d3d763 · outbound

This paper cites Predicting Aircraft Trajectories: A Deep Generative Convolutional Recurrent Neural Networks Approach.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Predicting Aircraft Trajectories: A Deep Generative Convolutional Recurrent Neural Networks Approach

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T15:16:51.069727Z

Source-reported events for the cited work

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Observation 7107a3cc-4900-4060-8677-5f573d7b9caa · outbound

This paper cites 3-d trajectory modeling for unmanned aerial vehicles,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network 3-d trajectory modeling for unmanned aerial vehicles,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.792746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 93004208-db47-41fd-9771-80af62cc3ca1 · outbound

This paper cites Short-term trajectory prediction methods,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Short-term trajectory prediction methods,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.769937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 90d875ff-cd86-42e6-bc3b-269e7bddb121 · outbound

This paper cites Airspace encounter models for estimating collision risk,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Airspace encounter models for estimating collision risk,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.747268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f25ff1f1-38b6-43c4-87e1-dae920f1c032 · outbound

This paper cites Learning probabilistic trajectory models of aircraft in terminal airspace from position data,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Learning probabilistic trajectory models of aircraft in terminal airspace from position data,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.721093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation aa125fe6-e97e-4192-820f-dbccaf597821 · outbound

This paper cites Attention is all you need,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Attention is all you need,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.698911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8e397064-cd54-4985-b68a-005e528ce257 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T15:16:51.115682Z

Source-reported events for the cited work

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Observation ef842cc8-16c6-4dc6-b1d8-0635ac6833f5 · outbound

This paper cites Graph Attention Networks.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Graph Attention Networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-12T15:16:51.122238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57154417-9d95-4a43-a477-ac41e0bc5fba · outbound

This paper cites Self-attention generative adversarial networks,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Self-attention generative adversarial networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.677204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8fec0c89-e142-4e62-a6e1-9a1c16d64db8 · outbound

This paper cites ViTGAN: Training GANs with Vision Transformers.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network ViTGAN: Training GANs with Vision Transformers

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T15:16:51.138205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f99cd10-4f40-41ab-a57c-e4d871455cd8 · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Fully convolutional networks for semantic segmentation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.657013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2152aace-1806-43be-962f-5923ea3c1f0d · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.631368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 23f74bfe-7d7d-48a0-86a7-c905a5dfc9c4 · outbound

This paper cites Deep residual learning for image recognition,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Deep residual learning for image recognition,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.612659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2ba95cb4-4580-42a1-a38b-15642bd31ded · outbound

This paper cites Densely connected convolutional networks,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Densely connected convolutional networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.589626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f5e688f7-282f-4836-8abc-4e30b82b61d2 · outbound

This paper cites Social gan: Socially acceptable trajectories with generative adversarial networks,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Social gan: Socially acceptable trajectories with generative adversarial networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.566097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0f269b13-40e0-4d29-b03a-922a6712754c · outbound

This paper cites Sophie: An attentive gan for predicting paths compliant to social and physical constraints,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Sophie: An attentive gan for predicting paths compliant to social and physical constraints,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.546592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation df350d20-d754-42e2-a375-365ab22c162d · outbound

This paper cites Conditional generative adversarial networks (CGAN) for aircraft trajectory prediction considering weather effects,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Conditional generative adversarial networks (CGAN) for aircraft trajectory prediction considering weather effects,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.522386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 61b8a2ea-67d8-4dee-aa97-c42f59e72955 · outbound

This paper cites Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.497130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1b98fdb7-a2ee-49f3-af79-1a638fd6ad42 · outbound

This paper cites Long short-term memory,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Long short-term memory,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.475095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 68eb71cb-48dc-4992-87d6-adfb461336cc · outbound

This paper cites Generative adversarial nets,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network Generative adversarial nets,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.454596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 18cdf1d2-1eca-4e28-b682-b7c402413528 · outbound

This paper cites On learning, representing, and generalizing a task in a humanoid robot,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network On learning, representing, and generalizing a task in a humanoid robot,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.432626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9ad8a2be-3578-4567-aa7f-d41f2c8007d2 · outbound

This paper cites gmr: Gaussian Mixture Regression,.

Landing Trajectory Prediction for UAS Based on Generative Adversarial Network gmr: Gaussian Mixture Regression,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:16:51.409014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.