Paper Citation Record · LEDGER

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications

As of 8 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2506.22360.

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

pith.paper-citation-record.v1
2506.22360 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:09:02.534956Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

16 of 16 outbound references displayed

verified exact0
verified fuzzy13
unresolved2
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 81c44fd0-ebde-488a-8ac7-3e99e0fb96e4 · outbound

This paper cites Retinomorphic event-based vision sensors: bioinspired cameras with spiking output,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications Retinomorphic event-based vision sensors: bioinspired cameras with spiking output,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:06.279573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c405040e-b931-4e4c-b93c-4a243d91c692 · outbound

This paper cites Collision detection for UAVs using event cameras,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications Collision detection for UAVs using event cameras,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:06.056884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5928c7c4-b384-45a5-83c0-f020a84d0664 · outbound

This paper cites Computer vision for autonomous vehicles: Problems, datasets and state of the art,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications Computer vision for autonomous vehicles: Problems, datasets and state of the art,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:05.729427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7c1c734d-ef55-4cfc-bb7e-3077fb0e6b50 · outbound

This paper cites Deep residual learning for image recognition,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications Deep residual learning for image recognition,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:05.499344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bb4fcccf-c938-420f-9c8d-1bfe0348068b · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T22:09:01.409174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f320bced-0efc-405d-8dad-ad6ae8e841ae · outbound

This paper cites A Large Scale Event-based Detection Dataset for Automotive.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications A Large Scale Event-based Detection Dataset for Automotive

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T22:09:01.498772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d027ec63-5407-4d35-9aee-93bec5670ad6 · outbound

This paper cites Discussion on event-based cameras for dynamic obstacles recognition and detection for UAVs in outdoor environments,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications Discussion on event-based cameras for dynamic obstacles recognition and detection for UAVs in outdoor environments,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:05.258233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 27c52030-7cdb-4b16-a955-80882ced381c · outbound

This paper cites End-to-end learning of representations for asynchronous event-based data,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications End-to-end learning of representations for asynchronous event-based data,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:04.991009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 16eb2bd7-d791-47d7-a1f3-672a7269c565 · outbound

This paper cites A differentiable recurrent surface for asynchronous event-based data,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications A differentiable recurrent surface for asynchronous event-based data,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:04.715159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dcda5a45-64d3-42cd-9811-c16d6d3f9d3a · outbound

This paper cites A Multi-Dimensional Covert Transaction Recognition Scheme for Blockchain,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications A Multi-Dimensional Covert Transaction Recognition Scheme for Blockchain,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:04.401949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fcf505d2-d59f-4096-87b1-3841f015ac0c · outbound

This paper cites Imagenet large scale visual recognition challenge,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications Imagenet large scale visual recognition challenge,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:04.113831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f00f41b5-64d3-40fe-b25a-ff4ef307e546 · outbound

This paper cites Evaluating collaborative filtering recommender systems,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications Evaluating collaborative filtering recommender systems,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:03.789239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1441bb7b-0b00-4220-b1bc-dc0c20138297 · outbound

This paper cites The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:03.471216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 873a92b5-e4f4-4781-a6e6-efee1e13133f · outbound

This paper cites The area under the precision-recall curve as a performance metric for rare binary events,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications The area under the precision-recall curve as a performance metric for rare binary events,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:03.157223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8f587e26-c3fd-4fe6-b1d2-6633a678b8ee · outbound

This paper cites Deep learning in news recommender systems: A comprehensive survey, challenges and future trends,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications Deep learning in news recommender systems: A comprehensive survey, challenges and future trends,

Reference 15

Resolution: malformed identifier; no resolver link, observed 2026-08-06T22:09:02.421724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb9bcae6-b5e3-4c2a-befa-ada9a02fc02b · outbound

This paper cites Dropout: a simple way to prevent neural networks from overfitting,.

From Ground to Air: Noise Robustness in Vision Transformers and CNNs for Event-Based Vehicle Classification with Potential UAV Applications Dropout: a simple way to prevent neural networks from overfitting,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:09:02.884198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.