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Paper Citation Record · LEDGER

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data

As of 16 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2411.09077.

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

pith.paper-citation-record.v1
2411.09077 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:09:59.341636Z

measured 57 of 57 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 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

57 of 57 outbound references displayed

  • verified exact3
  • verified fuzzy49
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9f6d31c0-fb9b-4f24-bd04-95e9672bd422 · outbound

This paper cites Increase in use of drones for prison smuggling,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Increase in use of drones for prison smuggling,

Reference 1

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation fb690aff-03fe-47f6-b68e-1228b588383f · outbound

This paper cites Drugs, weapons ’smuggled to prisoners by drone’,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Drugs, weapons ’smuggled to prisoners by drone’,

Reference 2

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation d5755641-ac8a-4a73-b975-82e18dd21f59 · outbound

This paper cites Heathrow airport: Drone sighting halts departures,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Heathrow airport: Drone sighting halts departures,

Reference 3

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Observation c2c19f6c-07f0-48fb-827d-72feb0abeb70 · outbound

This paper cites Flights diverted at East Midlands airport after drone sightings,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Flights diverted at East Midlands airport after drone sightings,

Reference 4

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation e4c106db-1cfa-42e3-a954-319e422ebf00 · outbound

This paper cites Dublin airport: Flights suspended for 30 minutes after drone sightings,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Dublin airport: Flights suspended for 30 minutes after drone sightings,

Reference 5

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Observation cdbce941-2b05-406c-be08-b036e7bfc31e · outbound

This paper cites UK Counter-Unmanned Aircraft Strategy,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data UK Counter-Unmanned Aircraft Strategy,

Reference 6

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Observation fc0b7e53-39a8-44c5-84b9-947075db4cea · outbound

This paper cites Defending Airports from UAS: A Survey on Cyber-Attacks and Counter-Drone Sensing Tech- nologies,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Defending Airports from UAS: A Survey on Cyber-Attacks and Counter-Drone Sensing Tech- nologies,

Reference 7

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation ae3f6457-9e4a-48b3-9c6c-7305a5d6d52f · outbound

This paper cites ImageNet classification with deep convolutional neural networks,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data ImageNet classification with deep convolutional neural networks,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.127721Z digest=sha256:2a3a14676d325d82faa1f906065921fb4bcc74689520daea90c0072c636e2240

Observation fef51cd3-a40c-4aa1-818a-eed10206cde1 · outbound

This paper cites You Only Look Once: Unified, Real-Time Object Detection,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data You Only Look Once: Unified, Real-Time Object Detection,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 98944eba-ba2f-465e-a094-471ddabcd589 · outbound

This paper cites YOLO9000: Better, Faster, Stronger,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data YOLO9000: Better, Faster, Stronger,

Reference 10

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 7ffc33e0-1703-41d9-af46-e94c3e1b47c8 · outbound

This paper cites SSD: Single Shot MultiBox Detector,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data SSD: Single Shot MultiBox Detector,

Reference 11

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.139155Z digest=sha256:96c29e84398dc5f7a3df8858d5897edd04dacf4de57cf3eed1ed0dc3cb6ecf3b

Observation ee4f2d5b-60e6-49d3-8fd1-49c36ac711f0 · outbound

This paper cites Fast R-CNN,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Fast R-CNN,

Reference 12

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.143105Z digest=sha256:69d1bffbae4579399b960bb633ed4d7e30efa7ae9c055964d8d23b16c453e380

Observation cef68868-403b-428f-a56c-ae4933a7b1f0 · outbound

This paper cites Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:09:59.147860Z digest=sha256:6c28227da52a6aa0d5e17d2d4a3d925ce7e2322292cb3eba7d2f5078ceab519a

Observation 8b111258-e9d7-4aaa-bc8a-ffcc795d90b1 · outbound

This paper cites Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Unmanned Aerial Vehicle Visual Detection and Tracking using Deep Neural Networks: A Performance Benchmark,

Reference 14

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.152153Z digest=sha256:d33b5251dfd1be6b6e345e7065153641bd9c44b16885152073866c2fe245d27e

Observation 3adc6508-6eda-4702-ae00-2494534ab5e6 · outbound

This paper cites Attention Is All You Need,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Attention Is All You Need,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.156314Z digest=sha256:a0e9148e5ad54f461d66d7041419aab010e98ec1f2ab76f1f2f3ff332881cc1d

Observation 837aa9ae-40a2-47b5-bbca-7566d4ae8846 · outbound

This paper cites End-to-End Object Detection with Transformers,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data End-to-End Object Detection with Transformers,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.160554Z digest=sha256:e92c24f41a7981a1647af3de42af651d5f8a3df3af058e6b0b7797baa1a29516

Observation 1fdeb694-56aa-4d72-9c6c-d2485237620d · outbound

This paper cites Towards Out-Of-Distribution Generalization: A Survey,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Towards Out-Of-Distribution Generalization: A Survey,

Reference 17

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.164702Z digest=sha256:fa85c06a5a6773141220237e96c7639a18cb92aeeefce90348a37729e476fdf6

Observation 82262cd6-00eb-4a7f-ac02-f82516695605 · outbound

This paper cites A Comprehensive Survey on Transfer Learning,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data A Comprehensive Survey on Transfer Learning,

Reference 18

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.169264Z digest=sha256:0e2007b2b7032a8678b5195607d7062049fb188012e717740f8b67046b796271

Observation 9821e417-923b-4bf2-a2e9-9fede08e7a88 · outbound

This paper cites Domain Adaptation for Visual Applications: A Comprehen- sive Survey,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Domain Adaptation for Visual Applications: A Comprehen- sive Survey,

Reference 19

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.173382Z digest=sha256:4b389525ad0fe6f2df4711ffb1f0c24f5cdbc132c46a5bfeee074e3d0ef494ac

Observation 225511dc-15cc-46b6-b82f-5a254fb987b8 · outbound

This paper cites Domain General- ization: A Survey,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Domain General- ization: A Survey,

Reference 20

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.178284Z digest=sha256:46b78fb8fe35a2c1686c3c3d313fadf9106546ae2e07b091f0bddd109315617c

Observation 7bfe6b0d-073f-4862-a771-374950fbfae8 · outbound

This paper cites Domain randomization for transferring deep neural networks from sim- ulation to the real world,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Domain randomization for transferring deep neural networks from sim- ulation to the real world,

Reference 21

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 20bc96ab-7d98-4212-82e3-0202ed064c19 · outbound

This paper cites Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:09:59.185848Z digest=sha256:713022e064eb6174755e3105da773a6e1f866d700853dab7f18a584b0f58c3df

Observation 0241026b-2b04-429f-bb4e-2ec5876930e0 · outbound

This paper cites Structured Domain Randomization: Bridging the Reality Gap by Context-Aware Synthetic Data,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Structured Domain Randomization: Bridging the Reality Gap by Context-Aware Synthetic Data,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.191721Z digest=sha256:713f189c7465c2907b4d3bac7c221348475b7a17f7a63c4bb04d0d1d82091186

Observation f95e9be3-5e9a-4296-9db6-12523c2f6a32 · outbound

This paper cites Applying Domain Randomization to Synthetic Data for Object Category Detection,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Applying Domain Randomization to Synthetic Data for Object Category Detection,

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.196874Z digest=sha256:1756ce3932df3bc7b836d92d81881f1f5a260af20115c6f40ead5f0019aca36f

Observation c73690a6-c206-41b3-919e-de8fc6c5c732 · outbound

This paper cites Benchmarking Domain Randomisation for Visual Sim-to-Real Transfer,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Benchmarking Domain Randomisation for Visual Sim-to-Real Transfer,

Reference 25

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.201144Z digest=sha256:7503e72d77c203e19d77c5db9fd8f7e1dc051d05e62df3eb20812585f28fe416

Observation 8781fbb6-5531-443e-b418-32310833ecba · outbound

This paper cites On Pre-Trained Image Features and Synthetic Images for Deep Learning.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data On Pre-Trained Image Features and Synthetic Images for Deep Learning

Reference 26

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local_arxiv, observed 2026-08-12T21:09:59.437939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 63829c2e-c99b-43d7-b4a8-f57b4f16a854 · outbound

This paper cites Drone Detection Using YOLOv5,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Drone Detection Using YOLOv5,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 487f1f2a-fe23-4c95-ae80-f1fd1037ad07 · outbound

This paper cites Detection and Recognition of Drones Based on a Deep Convolutional Neural Network Using Visible Imagery,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Detection and Recognition of Drones Based on a Deep Convolutional Neural Network Using Visible Imagery,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.213936Z digest=sha256:581eda75843a184a6feeb555edbe0f4824e86b3e625b3c99e28c1fa18c3f386e

Observation 0bc7e76a-7f7e-466f-8d05-36c28a995e2b · outbound

This paper cites An Object Detection Algorithm for Rotary- Wing UA V Based on AWin Transformer,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data An Object Detection Algorithm for Rotary- Wing UA V Based on AWin Transformer,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.218035Z digest=sha256:267357d99e8b919c3ed4d058f651cef03661b559870c1c54af04f8ab4cb5c8a6

Observation ce02ff3c-78c3-4bb0-b886-56d47af9f402 · outbound

This paper cites A Modified YOLOv4 Deep Learning Network for Vision-Based UA V Recognition,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data A Modified YOLOv4 Deep Learning Network for Vision-Based UA V Recognition,

Reference 30

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raw_fallback, observed 2026-08-12T21:09:59.801926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.223708Z digest=sha256:6227860b39893693307fbb320d7ca8758749f64f99111e7701b354a6b8769991

Observation b6e5da38-9167-46ca-8a16-24194bc70d4b · outbound

This paper cites Exploitation of data augmentation strategies for improved UA V detection,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Exploitation of data augmentation strategies for improved UA V detection,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.227596Z digest=sha256:78abc60307e66410666801a49448730ebc51fdc51acd5bfae565800103f1b3c2

Observation 09519139-071b-42bf-841a-617392d9844c · outbound

This paper cites Detecting aerial objects: Drones, birds, and helicopters,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Detecting aerial objects: Drones, birds, and helicopters,

Reference 32

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raw_fallback, observed 2026-08-12T21:09:59.777951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.231508Z digest=sha256:a324570a149d4c1a679303a2571cd5a3f26771799bfab5c6ac8c5e7015f4c732

Observation 6d6a099a-428f-40e6-bd8e-5205428b3f7a · outbound

This paper cites Small Flying Object Detection and Tracking in Digital Airport Tower through Spatial- Temporal ConvNets,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Small Flying Object Detection and Tracking in Digital Airport Tower through Spatial- Temporal ConvNets,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.235358Z digest=sha256:a053dea77f3557364cafd766983768188f8de2b2450db48fc28d92e1ab8e0de2

Observation 5f0bfb5b-8f14-4052-bbea-a62b1f7b7791 · outbound

This paper cites Spatio-Temporal Semantic Segmentation for Drone Detection,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Spatio-Temporal Semantic Segmentation for Drone Detection,

Reference 34

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raw_fallback, observed 2026-08-12T21:09:59.747050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.239621Z digest=sha256:2d898315822ab07988e2a9135b68502740c60818aae3f1584b2b0a884d5f60d5

Observation 795c7b50-34eb-4586-b39e-5b3db79dedf9 · outbound

This paper cites TransVisDrone: Spatio-Temporal Transformer for Vision-based Drone-to-Drone Detec- tion in Aerial Videos,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data TransVisDrone: Spatio-Temporal Transformer for Vision-based Drone-to-Drone Detec- tion in Aerial Videos,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.732057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.244390Z digest=sha256:3a7d888b2e7c284d0444ece0112ef3f0e774faa426241f085045e31da8a40066

Observation e3241ff1-86fe-4079-89a0-51bdbbb6cf66 · outbound

This paper cites On Rendering Synthetic Images for Training an Object Detector,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data On Rendering Synthetic Images for Training an Object Detector,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.719706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.248885Z digest=sha256:cadbc4c16297b20925482d5e6aae9a025936052f032bb1cbab38f129446cb628

Observation e4e017e9-306a-4883-a8ff-76a47131c054 · outbound

This paper cites UA V detection with a dataset augmented by domain randomization,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data UA V detection with a dataset augmented by domain randomization,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.706781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.253061Z digest=sha256:520a10c87bec9a62be5dbb4d762a9b750cd5c78be9b47fa1ad23d11b2e6fcb9e

Observation d4007aec-43c4-4f45-a9d3-f574729840e7 · outbound

This paper cites Using Images Rendered by PBRT to Train Faster R-CNN for UA V Detection,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Using Images Rendered by PBRT to Train Faster R-CNN for UA V Detection,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.692600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.256881Z digest=sha256:c553ab6d7135ebc02c19215d1c50dabf70d38f498b30fcf5eacc6f1248391c75

Observation b04678f8-d9d3-438a-b23d-4eb8eabc05d1 · outbound

This paper cites an unresolved cited work.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-12T21:09:59.680427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.261581Z digest=sha256:5f4467b7992ab2c908ab5a65dbf329110b11854708727110f7d4ffe457947c09

Observation c6cdc159-ed38-4648-b507-48dbc62be12c · outbound

This paper cites Quantifying the Simulation–Reality Gap for Deep Learning-Based Drone Detection,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Quantifying the Simulation–Reality Gap for Deep Learning-Based Drone Detection,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.666652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.265996Z digest=sha256:adbb0b675d0e76c729fe72788d604ff5533d107464ef4224e447b52eac5fef81

Observation 2b61df76-16dd-4864-96da-3473a86aa29d · outbound

This paper cites DronePose: The identification, segmentation, and orientation detection of drones via neural networks.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data DronePose: The identification, segmentation, and orientation detection of drones via neural networks

Reference 41

Resolution
verified exact
local_arxiv, observed 2026-08-12T21:09:59.418816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.271343Z digest=sha256:ee2ccc9754464f87d7043941519ba4f94758609538d51a50b8ccc1c8cce8721c

Observation 2315893c-1d87-46da-8953-a4ad362cdaf3 · outbound

This paper cites Scarce Data Driven Deep Learning of Drones via Generalized Data Distribution Space.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Scarce Data Driven Deep Learning of Drones via Generalized Data Distribution Space

Reference 42

Resolution
verified exact
local_arxiv, observed 2026-08-12T21:09:59.395949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.276142Z digest=sha256:f597d20bb8767b3d1a89c38d65acc9915a5cbcf3ce85ac0526a10a6993bdbcc4

Observation 5db4a0a3-bdea-4c5f-a86a-b82d6fe68109 · outbound

This paper cites Drone Detection Using Depth Maps,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Drone Detection Using Depth Maps,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.653295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.280354Z digest=sha256:6c071df8e0c0ebfd1ef8e09e9c1ac62abf02fa03bee6fa9bf4d6da8b897ce250

Observation 769fd070-6b0e-4b40-9eeb-49b15d8e5e11 · outbound

This paper cites Drone Model Classification Using Convolutional Neural Network Trained on Synthetic Data,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Drone Model Classification Using Convolutional Neural Network Trained on Synthetic Data,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.640074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.284906Z digest=sha256:0702fa55ae65de682c33009fa27da9dc721cb29976e412b34b22ef9f7489e19c

Observation cfb69e25-9766-4df6-9ed4-cfd65aeae792 · outbound

This paper cites Drone Model Identification by Convolutional Neural Network from Video Stream,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Drone Model Identification by Convolutional Neural Network from Video Stream,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.621450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.291055Z digest=sha256:668a6ebd34e2f17fbfe96742c790a4cafd040491aaf3ce14d1d9e9705714d693

Observation a87b68ae-9a9e-485b-9d28-ae6e81c0f4d0 · outbound

This paper cites Blender - a 3D modelling and rendering package.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Blender - a 3D modelling and rendering package

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.609244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.295447Z digest=sha256:c674aee53856ce329e7961f96e6410a8d5177ffc669089fa758dfddfa2418328

Observation e5db959b-7f43-4df3-a605-f22fa549f4b7 · outbound

This paper cites Microsoft COCO: Common Objects in Context,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Microsoft COCO: Common Objects in Context,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.596724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.300504Z digest=sha256:f1b2a844e403b163fc3bfa4d32704dcffc3f4c9927080235dd3d9e1a0b575069

Observation 46d2fb38-c929-48d9-9f5d-a1d4eab5d082 · outbound

This paper cites PyTorch: An Imperative Style, High- Performance Deep Learning Library,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data PyTorch: An Imperative Style, High- Performance Deep Learning Library,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.583023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.304781Z digest=sha256:ff5ffc810a29791c2ba18fc5bdcf7e02d58b401c8ebbf53fc431116e5b7d7bc2

Observation 0f218152-8070-4de5-a0f3-1d14299aa585 · outbound

This paper cites Vision/torchvision/models/detection/faster rcnn.py at main · pytorch/vision,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Vision/torchvision/models/detection/faster rcnn.py at main · pytorch/vision,

Reference 49

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verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.570494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.309251Z digest=sha256:1b423439ecc45464aae1548a0460e7f25cdc0bc885a3d4ad92a8b2636b887a6b

Observation 0e3c7204-5d9b-4c02-9096-d434044436b8 · outbound

This paper cites On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.556793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.313264Z digest=sha256:abcefd967d648a63bf974b58a3a5d019597924fe131d30247d3f946462c87f4c

Observation 999e9be8-3960-43a2-8a18-72a25a51690f · outbound

This paper cites Jung, “Imgaug,” Nov.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Jung, “Imgaug,” Nov

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.543560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.316822Z digest=sha256:81b55539e2f931b02d3f3c82d9d648c5770955c8219566d15164c61e07a862b5

Observation 39e8f535-e428-4d53-afba-9c2ffba24d35 · outbound

This paper cites Adaptive Inattentional Framework for Video Object Detection With Reward-Conditional Training,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Adaptive Inattentional Framework for Video Object Detection With Reward-Conditional Training,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.531490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.320889Z digest=sha256:d377b62f4db4a11d429483a358e0c1f7686be8fdd5eb4c8125d3b9b3efd83555

Observation c684c384-4fed-4a96-8260-51efaa7c78ad · outbound

This paper cites Drone-vs-Bird Detection Challenge at IEEE A VSS2019,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Drone-vs-Bird Detection Challenge at IEEE A VSS2019,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.519100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.324545Z digest=sha256:9bb2fe71b574bdb9cf79a2900f741744ba85ed06d6d03f733a0862c4ff6b875d

Observation d15e10c9-2211-4e00-b027-875b035c8be9 · outbound

This paper cites Drone vs. Bird Detection: Deep Learning Algorithms and Results from a Grand Challenge,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Drone vs. Bird Detection: Deep Learning Algorithms and Results from a Grand Challenge,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.505209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.328635Z digest=sha256:37bdd9018da18c5086b6adfea3c1f31df478843e4b823df6c27de7a9cd440523

Observation 3571e08a-706c-4fe0-a872-d144f6e0c56b · outbound

This paper cites Anti-UAV: A Large Multi-Modal Benchmark for UAV Tracking.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Anti-UAV: A Large Multi-Modal Benchmark for UAV Tracking

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-12T21:09:59.332596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:09:59.332596Z digest=sha256:c377df9d8c31457f78ae14c1bb70cc7db2c27c5c323014b382972d0acb15b125

Observation 26b530d4-0750-4a0f-853e-d633daae9297 · outbound

This paper cites Torch.manual seed(3407) is all you need: On the influence of random seeds in deep learning architectures for computer vision,.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Torch.manual seed(3407) is all you need: On the influence of random seeds in deep learning architectures for computer vision,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T21:09:59.491067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.337245Z digest=sha256:7d14c7f07d9da3b249e6bc5a783dbe790f61ed6ec8844b40f3ae16207102c690

Observation 4e2b3d2d-1dc7-466b-a5cd-df8604d350aa · outbound

This paper cites an unresolved cited work.

Drone Detection using Deep Neural Networks Trained on Pure Synthetic Data Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-12T21:09:59.476891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-12T21:09:59.341636Z digest=sha256:da32498e7fb4c30ad37c0f1f91d5cbf0edf868579994bba3de4683c8eeb6c28e

Pith citing papers

No inbound Pith citation observations are available.