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Paper Citation Record · LEDGER

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data

As of 16 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2607.02636.

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

pith.paper-citation-record.v1
2607.02636 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T08:12:59.937555Z

measured 37 of 37 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved35
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b519a9d8-7024-43cb-bcbc-3540500e4145 · outbound

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

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Faster r-cnn: Towards real-time object detection with region proposal networks’’

Reference 1

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Observation 1708ce2e-2466-45df-a219-b54a29f53149 · outbound

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

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘You only look once: Unified, real-time object detection’’

Reference 2

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Observation e0d298dc-c146-48af-89e8-08fde9df9ddd · outbound

This paper cites YOLOv3: An Incremental Improvement.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data YOLOv3: An Incremental Improvement

Reference 3

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Observation 676aa384-944f-4624-b250-d38fcec5d20d · outbound

This paper cites Version 8.0.0.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data Version 8.0.0

Reference 4

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Observation 6a662db5-d0d6-43b2-94cc-4cf8adb0e986 · outbound

This paper cites ‘‘Focal loss for dense object detection’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Focal loss for dense object detection’’

Reference 5

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source=pdf_text observed=2026-07-12T08:12:59.937555Z digest=sha256:b9f050f008f8d5ea2d1c0ef983b0920bb6090a17e150299562096cb66fad02c1

Observation 9ea049b2-038f-49d5-9a2e-1f3fa39495b2 · outbound

This paper cites Vision Meets Drones: A Challenge.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data Vision Meets Drones: A Challenge

Reference 6

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Observation a413824e-fffd-4f6e-bb18-62a8ae33e308 · outbound

This paper cites ‘‘Object detection with deep learning: A review’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Object detection with deep learning: A review’’

Reference 7

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Observation 7c026a69-78ef-4591-8b1d-e69ab5905721 · outbound

This paper cites ‘‘Generalized uav object detection via frequency domain disentanglement’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Generalized uav object detection via frequency domain disentanglement’’

Reference 8

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Observation f28a721e-4c41-45b3-85a6-fdc13e4c4c6e · outbound

This paper cites an unresolved cited work.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data Unresolved cited work

Reference 9

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Observation 7c90b11f-d82d-41cf-8066-a843679b34ba · outbound

This paper cites an unresolved cited work.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data Unresolved cited work

Reference 10

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source=pdf_text observed=2026-07-12T08:12:59.937555Z digest=sha256:776f403847148148d5c8049e2c69798a67e9a46c830782107b0e26f44522638c

Observation 0c6d1871-2586-46c2-9846-8de81d824d1c · outbound

This paper cites ‘‘Communication-efficient learning of deep networks from decentralized data’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Communication-efficient learning of deep networks from decentralized data’’

Reference 11

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Observation 62a1ba1c-1af9-4f4a-ad8b-f00fdfd7d60f · outbound

This paper cites ‘‘Federated machine learning: Concept and applications’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Federated machine learning: Concept and applications’’

Reference 12

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Observation 2518171c-ed3b-4553-af6a-10945e95c565 · outbound

This paper cites ‘‘Fedvision: An online visual object detection platform powered by federated learning’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Fedvision: An online visual object detection platform powered by federated learning’’

Reference 13

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source=pdf_text observed=2026-07-12T08:12:59.937555Z digest=sha256:84eb35573c2020ce7b17865772debc9f393cc3ec37ce1b3ed3fd83737234ff75

Observation 56b989d1-8635-4903-851e-40a4bc449759 · outbound

This paper cites https://www.kaggle.com/datasets/sudipchakrabarty/kiit- mita.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data https://www.kaggle.com/datasets/sudipchakrabarty/kiit- mita

Reference 14

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Observation bf9f3f5b-4bfc-4353-8fb5-dbb6e127edea · outbound

This paper cites ‘‘Rich feature hierarchies for accurate object detection and semantic segmentation’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Rich feature hierarchies for accurate object detection and semantic segmentation’’

Reference 15

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Observation 21d15811-8262-495e-9080-dc5d23bf4a2d · outbound

This paper cites ‘‘Fast r-cnn’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Fast r-cnn’’

Reference 16

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Observation 95f38429-c33d-4549-ae19-1cc5336107f3 · outbound

This paper cites ‘‘Ssd: Single shot multibox detector’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Ssd: Single shot multibox detector’’

Reference 17

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Observation f3a3e2e7-58b1-4683-86e1-771c4e129f6a · outbound

This paper cites Version 7.0.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data Version 7.0

Reference 18

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-07-12T08:12:59.937555Z digest=sha256:3660babeae11546034018b360513363bd1638acf1702e5e75d961703cfaa296a

Observation 062b2ccb-0a20-4875-8081-2c93b2060fb8 · outbound

This paper cites Version 11.0.0.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data Version 11.0.0

Reference 19

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Observation 7431a58c-c3ce-4862-bf16-b445a2e5d4e1 · outbound

This paper cites Version 26.0.0.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data Version 26.0.0

Reference 20

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Observation 97881e38-16a2-49c7-9276-3e55d1b91477 · outbound

This paper cites ‘‘Fcos: Fully convolutional one-stage object detection’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Fcos: Fully convolutional one-stage object detection’’

Reference 21

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source=pdf_text observed=2026-07-12T08:12:59.937555Z digest=sha256:d43c4da1a7b97533d55a7b0aa6e67714937e070510134885412e3adb820bb722

Observation 8b4a144c-9b10-4ae8-855e-0fcde294b020 · outbound

This paper cites ‘‘End-to-end object detection with transformers’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘End-to-end object detection with transformers’’

Reference 22

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Observation cf20ef9c-ab55-4d5b-b558-de68b95d24b9 · outbound

This paper cites ‘‘Recent advances for aerial object detection: A survey’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Recent advances for aerial object detection: A survey’’

Reference 23

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Observation c8dae464-7961-4593-89c4-be765cec5a56 · outbound

This paper cites ‘‘Microsoft coco: Common objects in context’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Microsoft coco: Common objects in context’’

Reference 24

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Observation 8cda7333-0fea-44b1-ac4b-83745d5a0d94 · outbound

This paper cites ‘‘The pascal visual object classes (voc) challenge’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘The pascal visual object classes (voc) challenge’’

Reference 25

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Observation a2a5f6d4-0c84-4fb1-ba42-63ec17328a2b · outbound

This paper cites ‘‘Drones in defense: Real-time vision-based military target surveillance and tracking’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Drones in defense: Real-time vision-based military target surveillance and tracking’’

Reference 26

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Observation 09b03645-fb63-4bc0-9ac4-11a9cd6ca21c · outbound

This paper cites ‘‘Development of real-time unmanned aerial vehicle urban object detection system with federated learning’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Development of real-time unmanned aerial vehicle urban object detection system with federated learning’’

Reference 27

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Observation dc3a13fc-463f-4e10-9cdd-dd4eabec7e9f · outbound

This paper cites ‘‘Improving Federated Learning UAV Urban Object Detection System via Data Heterogeneity Mitigation’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Improving Federated Learning UAV Urban Object Detection System via Data Heterogeneity Mitigation’’

Reference 28

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Observation 762ae7c0-f427-4161-8895-35ebe4baf320 · outbound

This paper cites ‘‘Federated learning with non-iid data: A survey’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Federated learning with non-iid data: A survey’’

Reference 29

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Observation dc795426-baee-4eb6-ba77-cbaa5605edbf · outbound

This paper cites LEAF: A Benchmark for Federated Settings.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data LEAF: A Benchmark for Federated Settings

Reference 30

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Observation 7b9bed88-66cf-4a3f-930b-e4d6cc534f36 · outbound

This paper cites ‘‘Federated learning: Challenges, methods, and future directions’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Federated learning: Challenges, methods, and future directions’’

Reference 31

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Observation de3c0e36-e382-45b0-8c97-85940336d9d7 · outbound

This paper cites ‘‘Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data’’

Reference 32

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Observation 9437dec0-9d4f-4d7a-8f27-3c7918245aff · outbound

This paper cites ‘‘Federated learning on non-IID data: A survey’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Federated learning on non-IID data: A survey’’

Reference 33

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Observation dfa93af6-45ec-44ff-8dce-cdf826692306 · outbound

This paper cites 2023.url:https://github.com/ ultralytics/ultralytics.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data 2023.url:https://github.com/ ultralytics/ultralytics

Reference 34

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Observation 1a435b30-dcb2-4686-90cc-0cef9b02b279 · outbound

This paper cites ‘‘FedArtML: A Tool to Facilitate the Generation of Non-IID Datasets in a Controlled Way to Support Federated Learning Research’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘FedArtML: A Tool to Facilitate the Generation of Non-IID Datasets in a Controlled Way to Support Federated Learning Research’’

Reference 35

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Observation 27bc0d04-cf1e-4072-b7cc-0f9fc69b92a1 · outbound

This paper cites ‘‘Client selection and bandwidth allocation in wireless federated learning networks: A long-term perspective’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Client selection and bandwidth allocation in wireless federated learning networks: A long-term perspective’’

Reference 36

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Observation 0fecbbc8-4829-476a-9ee4-98dd85b9939c · outbound

This paper cites ‘‘Wireless federated learning over resource-constrained networks: Digital versus analog transmissions’’.

Federated Learning for Object Detection: Enabling Collaborative Drone Learning Without Centralizing Data ‘‘Wireless federated learning over resource-constrained networks: Digital versus analog transmissions’’

Reference 37

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source=pdf_text observed=2026-07-12T08:12:59.937555Z digest=sha256:22b5890a6a5d730276962779df8030250cbfb74d4c7b574a1372f4c1cda836db

Pith citing papers

No inbound Pith citation observations are available.