Paper Citation Record · LEDGER

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles

As of 15 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2412.07655.

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

pith.paper-citation-record.v1
2412.07655 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:42:56.174787Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:17:04.228041Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T18:17:04.313739Z

Reference resolution

46 of 46 outbound references displayed

verified exact1
verified fuzzy38
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6dba1ea5-0288-4795-a419-6d0db0e4eca6 · outbound

This paper cites A survey of deep learning techniques for autonomous driving,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles A survey of deep learning techniques for autonomous driving,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.765486Z

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Observation 427e9658-7280-4049-8ba6-c6995baeca94 · outbound

This paper cites You only look once: Unified, real-time object detection,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles You only look once: Unified, real-time object detection,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.756384Z

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Observation 6c61d3fe-75c5-4358-879d-28477fff2e47 · outbound

This paper cites YOLO9000: better, faster, stronger,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles YOLO9000: better, faster, stronger,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.746613Z

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Observation aaab23c2-4499-4d76-9fd4-b8d9d55d817e · outbound

This paper cites YOLOv5: You Only Look Once version 5,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles YOLOv5: You Only Look Once version 5,

Reference 4

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Observation 01e4383c-9844-455a-b0d1-1b65f7166310 · outbound

This paper cites YOLOv8: You Only Look Once version 8,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles YOLOv8: You Only Look Once version 8,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.724229Z

Source-reported events for the cited work

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Observation 55c0b6c6-8d0a-4171-ae70-54478d992180 · outbound

This paper cites Robust Object Detection in Challenging Weather Conditions,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Robust Object Detection in Challenging Weather Conditions,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.713494Z

Source-reported events for the cited work

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Observation ea4595a8-d4b4-4572-8332-a2e6f90e4a0e · outbound

This paper cites How to Train a Defect Detection Model Using Synthetic Data with NVIDIA Om- niverse Replicator,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles How to Train a Defect Detection Model Using Synthetic Data with NVIDIA Om- niverse Replicator,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.702972Z

Source-reported events for the cited work

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Observation 26671900-5ac2-4daf-a728-4a382665409f · outbound

This paper cites Digitaltwinofanindustrialworkstation: Anovelmethodofanauto-labeled data generator using virtual reality for human action recognition in the context of human–robot collaboration,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Digitaltwinofanindustrialworkstation: Anovelmethodofanauto-labeled data generator using virtual reality for human action recognition in the context of human–robot collaboration,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.692510Z

Source-reported events for the cited work

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Observation 92e21161-ffde-49a0-a036-f1e951e22e6a · outbound

This paper cites Efficient Development of Simulated Environments for Autonomous Vehicle Training,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Efficient Development of Simulated Environments for Autonomous Vehicle Training,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.682048Z

Source-reported events for the cited work

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Observation eecad1ce-1e07-4ff1-9442-9807b2dde2ca · outbound

This paper cites The Computational Limits of Deep Learning.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles The Computational Limits of Deep Learning

Reference 10

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Source-reported events for the cited work

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Observation 9c3dcea3-a29a-4656-a404-5706419e6b35 · outbound

This paper cites A Tutorial on Bayesian Optimization.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles A Tutorial on Bayesian Optimization

Reference 11

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Observation a88be8cb-17ec-4196-b559-fcaeb6c4d82c · outbound

This paper cites Automatic Tuning of Hyperparameters Using Bayesian Optimization,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Automatic Tuning of Hyperparameters Using Bayesian Optimization,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.670806Z

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Observation cf4d7352-ae88-4715-bc8b-f29622e9f00b · outbound

This paper cites CARLA: An Open Urban Driving Simulator,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles CARLA: An Open Urban Driving Simulator,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.659007Z

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Observation 4d6d631e-f3b9-496e-8c85-723e9b45ca73 · outbound

This paper cites Generic Urban Air Mobility (GUAM),.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Generic Urban Air Mobility (GUAM),

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.647784Z

Source-reported events for the cited work

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Observation 3bc659bc-329f-445c-a62f-8a8dea159785 · outbound

This paper cites ADA: Adversarial Data Augmentation for Object Detection,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles ADA: Adversarial Data Augmentation for Object Detection,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.626017Z

Source-reported events for the cited work

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Observation c55e26be-bbba-425f-bc27-baf9dc683ce4 · outbound

This paper cites Closing the Visual Sim-to-Real Gap with Object-Composable NeRFs.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Closing the Visual Sim-to-Real Gap with Object-Composable NeRFs

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-11T18:42:56.303794Z

Source-reported events for the cited work

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Observation 52b1e81b-4185-4e3c-a7b5-e311b575a2f6 · outbound

This paper cites Deep learning on a data diet: Finding important examples early in training,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Deep learning on a data diet: Finding important examples early in training,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.616195Z

Source-reported events for the cited work

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Observation 67c40b69-62b3-43bf-8f51-e8ed306dcd9a · outbound

This paper cites Prioritized training on points that are learnable, worth learning, and not yet learnt,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Prioritized training on points that are learnable, worth learning, and not yet learnt,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.606553Z

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Observation dd312464-bb72-4401-aa4c-f2be2599104a · outbound

This paper cites Deepcore: A comprehensive library for coreset selection in deep learning,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Deepcore: A comprehensive library for coreset selection in deep learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.596322Z

Source-reported events for the cited work

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Observation b78debc4-1987-4421-9858-78c351cc3197 · outbound

This paper cites Beyond neural scaling laws: beating power law scaling via data pruning,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Beyond neural scaling laws: beating power law scaling via data pruning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.584619Z

Source-reported events for the cited work

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Observation 70226991-f8c8-4482-ab09-355bb2898e22 · outbound

This paper cites Towards Accelerated Model Training via Bayesian Data Selection,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Towards Accelerated Model Training via Bayesian Data Selection,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.572547Z

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Observation be5bac79-8c47-4a3b-a2d0-02936b78c15f · outbound

This paper cites Taking the human out of the loop: A review of Bayesian optimization,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Taking the human out of the loop: A review of Bayesian optimization,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.560558Z

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Observation b50cf59a-aa24-4f8e-9f34-d3d8574a1f5a · outbound

This paper cites Practical bayesian optimization of machine learning algorithms,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Practical bayesian optimization of machine learning algorithms,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.548830Z

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Observation 2fe918ae-5b5a-4d61-ad96-4969d70fbba7 · outbound

This paper cites Uncertainty Quantification-Based Switching Control Method for Vision-Based Object Tracking in Unmanned Aerial Vehicles,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Uncertainty Quantification-Based Switching Control Method for Vision-Based Object Tracking in Unmanned Aerial Vehicles,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.537799Z

Source-reported events for the cited work

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Observation 04c450e9-0b9e-4be3-9c68-e9c4ac614311 · outbound

This paper cites Design and analysis of a novelL1 adaptive control architecture with guaranteed transient performance,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Design and analysis of a novelL1 adaptive control architecture with guaranteed transient performance,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.526757Z

Source-reported events for the cited work

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Observation b38c2e95-4872-4713-a664-9878d2cd69b9 · outbound

This paper cites Fine-TuningofNeuralNetworkApproximate MPC without Retraining via Bayesian Optimization,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Fine-TuningofNeuralNetworkApproximate MPC without Retraining via Bayesian Optimization,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.515090Z

Source-reported events for the cited work

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Observation 65634576-c2e3-4ad2-978d-a2c7db31bb07 · outbound

This paper cites Learning-based nonlinear model predictive control to improve vision-based mobile robot path-tracking in challenging outdoor environments,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Learning-based nonlinear model predictive control to improve vision-based mobile robot path-tracking in challenging outdoor environments,

Reference 27

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Observation 23d88fc9-e95c-4dd9-8850-0a950c0e6b74 · outbound

This paper cites A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS

Reference 28

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Source-reported events for the cited work

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This paper cites HelipadCat: Categorised Helipad Image Dataset and Detection Method,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles HelipadCat: Categorised Helipad Image Dataset and Detection Method,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.504310Z

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Observation 53c38444-3cbe-462a-acd7-bb00e4e4d889 · outbound

This paper cites URL https://docs.ultralytics.com/usage/cfg/, accessed: 2024-12-01.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles URL https://docs.ultralytics.com/usage/cfg/, accessed: 2024-12-01

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.493728Z

Source-reported events for the cited work

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Observation 81536dfc-ce41-4b50-9603-5b9120cc8730 · outbound

This paper cites State of the Art: Reproducibility in Artificial Intelligence,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles State of the Art: Reproducibility in Artificial Intelligence,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.482811Z

Source-reported events for the cited work

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Observation 3ff7195b-a22b-47be-8063-8d1503284e0a · outbound

This paper cites A practical taxonomy of reproducibility for machine learning research,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles A practical taxonomy of reproducibility for machine learning research,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.472314Z

Source-reported events for the cited work

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Observation 32e74820-12e2-4696-9c60-5b8a2b6aa354 · outbound

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Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Unresolved cited work

Reference 33

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Observation df3dc59e-5292-4ce1-a3d3-53fe89236630 · outbound

This paper cites Microsoft coco: Common objects in context,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Microsoft coco: Common objects in context,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.448694Z

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Observation ded9a1a4-08cf-4b47-bb12-c24a82d9b443 · outbound

This paper cites Random forests,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Random forests,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.437097Z

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Observation 92bd6427-580c-46b7-907c-c36fcb70e346 · outbound

This paper cites Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Aleatoric and Epistemic Uncertainty in Machine Learning: An Introduction to Concepts and Methods

Reference 36

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Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Unreal Engine,

Reference 37

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Observation 49ee0aac-c5bf-46e2-bc60-f9230148d5d9 · outbound

This paper cites JAX-GUAM: General Uncertainty Approximation Models,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles JAX-GUAM: General Uncertainty Approximation Models,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.414510Z

Source-reported events for the cited work

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Observation ed73f05e-3de0-4b9c-ac65-199dfe0b6fa8 · outbound

This paper cites PyTorch: AnImperativeStyle,High-PerformanceDeepLearningLibrary,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles PyTorch: AnImperativeStyle,High-PerformanceDeepLearningLibrary,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.403208Z

Source-reported events for the cited work

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Observation fd642afc-0154-428d-98ae-115fc489ffb7 · outbound

This paper cites Robotic Operating System,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Robotic Operating System,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.391522Z

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Observation 7de3214d-df9f-41b9-9dac-0a3207612f64 · outbound

This paper cites Simple online and realtime tracking,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Simple online and realtime tracking,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.380211Z

Source-reported events for the cited work

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Observation 76b2ed7d-2d3a-4d03-805c-692d49c127ca · outbound

This paper cites J., and Murray, R.,Feedback systems: an introduction for scientists and engineers, Princeton university press, 2021.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles J., and Murray, R.,Feedback systems: an introduction for scientists and engineers, Princeton university press, 2021

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.368967Z

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Observation 61c2b834-7709-4a27-8833-20ccb900b1e9 · outbound

This paper cites Simulation and PID control of a Stewart platform with linear motor,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Simulation and PID control of a Stewart platform with linear motor,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.357381Z

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Observation 9bbe7825-005b-4977-ac19-ed63912a1832 · outbound

This paper cites Gaussian processes for machine learning (GPML) toolbox,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Gaussian processes for machine learning (GPML) toolbox,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.346124Z

Source-reported events for the cited work

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Observation dd2bfd8d-e508-4b81-8190-d4e5274d147f · outbound

This paper cites Bayesian Optimization: Open source constrained global optimization tool for Python,.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Bayesian Optimization: Open source constrained global optimization tool for Python,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T18:42:56.335876Z

Source-reported events for the cited work

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Observation 3558fcd9-f018-426f-ba0b-9cd7c84564c5 · outbound

This paper cites an unresolved cited work.

Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-11T18:42:56.636167Z

Source-reported events for the cited work

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Pith citing papers

Observation 1932d22b-bbfa-43a8-ac04-44f114e0f48a · inbound

Verification and Validation of a Vision-Based Landing System for Autonomous VTOL Air Taxis cites this paper.

Verification and Validation of a Vision-Based Landing System for Autonomous VTOL Air Taxis Bayesian Data Augmentation and Training for Perception DNN in Autonomous Aerial Vehicles

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-11T18:17:04.322075Z

Source-reported events for the cited work

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