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Paper Citation Record · LEDGER

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

As of 14 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 2026-08-14T06:32:32.682623+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
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

Unavailable: canonical work link unavailable.

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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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no resolver link, observed 2026-08-11T18:42:56.047389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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raw_fallback, observed 2026-08-11T18:42:56.647784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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raw_fallback, observed 2026-08-11T18:42:56.626017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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raw_fallback, observed 2026-08-11T18:42:56.606553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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raw_fallback, observed 2026-08-11T18:42:56.596322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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raw_fallback, observed 2026-08-11T18:42:56.584619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.091530Z digest=sha256:261c871b23db076094b07376b3fd94a9eb3f7ed1b98e634ea066338f779ddbd4

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:42:56.109741Z digest=sha256:4c77033125948442fce82a03cc229dd99a18383968851a8dfc04721827e6f600

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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unresolved
no resolver link, observed 2026-08-11T18:42:56.113425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:42:56.113425Z digest=sha256:65afa6e660bcd971216b88ee5d34f0c1daf96c10e70ed96b643e544d40796026

Observation 2132f5be-6093-45eb-8bb4-eb79622b44d5 · outbound

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

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raw_fallback, observed 2026-08-11T18:42:56.504310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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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

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raw_fallback, observed 2026-08-11T18:42:56.493728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.120850Z digest=sha256:db93ea9322835e71ff487d10ce9f95513a0e5918a3ed852379b09316d78bd707

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

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raw_fallback, observed 2026-08-11T18:42:56.482811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.124538Z digest=sha256:7684b6f34f5033aac34165fbe17bf66fbc41515a9d8d61687123ed7b2ed13375

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.128064Z digest=sha256:01b0af681cdc06efbca588ab66ff2028ad251456d47c3647956d1dc7f921e6dc

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

This paper cites an unresolved cited work.

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

Reference 33

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unresolved
raw_fallback, observed 2026-08-11T18:42:56.460791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.131735Z digest=sha256:0cc61e0fafd45434140b858878e70cde0aa2ac9fc496f2905bfde7d65bd78d39

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.135433Z digest=sha256:d7274e8fc8add04ce66189293f5b327b3feb44b2e5d31141f1e29b894b7c96b1

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.138810Z digest=sha256:6347945604d1dc49295fcee4b15dbbdbcd0c783a6ab0c89071dfa2ef38f9bc37

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

Resolution
unresolved
no resolver link, observed 2026-08-11T18:42:56.142661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:42:56.142661Z digest=sha256:7f1cb9c06c0482a9dbc56b9d284769949ee99a67d11173255c9a02615809755f

Observation b03321b8-1027-4907-9a6b-cbd47f362389 · outbound

This paper cites Unreal Engine,.

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

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:42:56.425627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.146431Z digest=sha256:d8aefc5f4ebd70d45e9f2d9748fbdf0feb40688625d3b77840ce304344fa0910

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

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.150038Z digest=sha256:e574df5c9d0cb354a16d8859f2133ab3606d7f4fd927be7b38c407139ad9efb6

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

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.153641Z digest=sha256:0a2fa5d406dc179a076cd6b0ee061f354386d0e0266d504d2920c1304401886a

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.157142Z digest=sha256:813c7726914d8c4bdbd9f52a2c7192b9f2a89525ec7dc8ebebb6ca8084e77ea3

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

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.160712Z digest=sha256:65d7fe939f90a3c732298f4bf714a447cefacfdd12aeb227db3a69af9134016a

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.164201Z digest=sha256:421da5f885bdadd899decc1fecd7a3d473b2574cc2e1efdfceae799d54f107e5

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.167616Z digest=sha256:9a6c0c053b4d6cd5efbbe177d0b473eb099431ef420350e2894d5ec9c6a0abf4

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

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.171291Z digest=sha256:4ddfbeea27d947eaf66fad34823140d37fc285c60862ad848cb7c49b40e07cfa

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

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.174787Z digest=sha256:7013067a56be25a5bc1ceb405d6827083dcc69bdfb05c3cd31c1ab2f64f19f3b

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

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:42:56.062409Z digest=sha256:2ee93ed04eb2f722387bc41fa064e2638d0f7350b36b8077c1ebf849a86cbba0

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

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-11T18:17:04.228041Z digest=sha256:23bfd589d99ee4fb6ba5ec210dc30218def5a0881942c07ac3bc98cbbc6def9d