Paper Citation Record · LEDGER

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys

As of 21 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2505.10737.

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

pith.paper-citation-record.v1
2505.10737 v1

Coverage vector

measured 42 of 42 reference resolution

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measured 42 of 42 standing notices

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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

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Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation f09dfe8c-30b3-4cc3-9112-f1023b8e2484 · outbound

This paper cites Abraham and Katrin Berkenbusch.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Abraham and Katrin Berkenbusch

Reference 1

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Observation 21f5fe1d-5205-4782-807e-618114a70884 · outbound

This paper cites Slicing aided hyper inference and fine-tuning for small object detection.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Slicing aided hyper inference and fine-tuning for small object detection

Reference 2

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Observation 752c2792-64c5-4556-b5ee-f60ebbcae11c · outbound

This paper cites CountGD: Multi-modal open-world counting.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys CountGD: Multi-modal open-world counting

Reference 3

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This paper cites Barber-Meyer, Gerald L.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Barber-Meyer, Gerald L

Reference 4

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This paper cites Efficient Pipeline for Camera Trap Image Review.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Efficient Pipeline for Camera Trap Image Review

Reference 5

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Observation e7d4df97-b243-41fc-8c4b-c7b2a38ed5fe · outbound

This paper cites Fretwell, Geoffrey French, and Michal Mackiewicz.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Fretwell, Geoffrey French, and Michal Mackiewicz

Reference 6

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Observation 7d6cfdfe-79f8-4bc3-b74e-d44f80a5c96d · outbound

This paper cites Brack, Andreas Kindel, and Luiz Flamarion B.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Brack, Andreas Kindel, and Luiz Flamarion B

Reference 7

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Observation fadfb35b-1312-4833-abe9-4155a9b73b97 · outbound

This paper cites Appli- cations for deep learning in ecology.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Appli- cations for deep learning in ecology

Reference 8

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Observation 5f25cb99-fc47-48b2-ab5a-d54a0b332709 · outbound

This paper cites Automated detection of wildlife using drones: Synthesis, opportunities and constraints.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Automated detection of wildlife using drones: Synthesis, opportunities and constraints

Reference 9

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Observation 7b1e0399-069d-4bbf-bc35-2830813cbdb2 · outbound

This paper cites Cubaynes, Peter T.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Cubaynes, Peter T

Reference 10

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Observation a09dd6a4-8556-443e-b021-cffdc1485e39 · outbound

This paper cites an unresolved cited work.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Unresolved cited work

Reference 11

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Observation 8ab24d71-ce30-4a27-983d-5a917f8af191 · outbound

This paper cites Mac- donald, and Tiejun Wang.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Mac- donald, and Tiejun Wang

Reference 12

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This paper cites BaboonLand Dataset: Tracking pri- mates in the wild and automating behaviour recognition from drone videos, 2024.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys BaboonLand Dataset: Tracking pri- mates in the wild and automating behaviour recognition from drone videos, 2024

Reference 13

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Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Unresolved cited work

Reference 14

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Observation ce4afddc-c83b-440f-bfee-4f940370cbfe · outbound

This paper cites Fretwell, Paul Scofield, and Richard A.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Fretwell, Paul Scofield, and Richard A

Reference 15

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Observation 1050eadf-235a-4e1f-983d-6f4be5015035 · outbound

This paper cites Gray, Kevin C.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Gray, Kevin C

Reference 16

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Observation b004039e-120d-4413-aebc-74a9cec4aa70 · outbound

This paper cites Gray, Abram B.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Gray, Abram B

Reference 17

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Observation 83ee30c7-1045-49c6-a2c0-0f866dddf144 · outbound

This paper cites Drones and deep learning produce accurate and efficient monitoring of large- scale seabird colonies.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Drones and deep learning produce accurate and efficient monitoring of large- scale seabird colonies

Reference 18

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Observation bf6899be-04fa-45a8-9416-84f27e2bf05e · outbound

This paper cites Deep Residual Learning for Image Recognition.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Deep Residual Learning for Image Recognition

Reference 19

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This paper cites Pytorch-Wildlife: A collab- orative deep learning framework for conservation, 2024.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Pytorch-Wildlife: A collab- orative deep learning framework for conservation, 2024

Reference 20

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Observation 2f791b59-76cd-4ae9-8edc-3b2042786804 · outbound

This paper cites Hodgson, Rowan Mott, Shane M.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Hodgson, Rowan Mott, Shane M

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:07:22.883422Z

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Observation 5d7d600b-a998-4bf7-8e40-d96b3f9485ae · outbound

This paper cites Application of Deep-Learning meth- ods to bird detection using unmanned aerial vehicle imagery.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Application of Deep-Learning meth- ods to bird detection using unmanned aerial vehicle imagery

Reference 22

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Observation d567eade-eaa6-4ffd-9bd8-b8cf2dd2e814 · outbound

This paper cites Thalassarche salvini.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Thalassarche salvini

Reference 23

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Observation 14b0e20b-6672-45d3-958f-b4c46ce6c714 · outbound

This paper cites Eudyptes sclateri.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Eudyptes sclateri

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:07:22.821427Z

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Observation 3dbe8c67-5cbd-47b6-bc11-72bd6476def5 · outbound

This paper cites Babu, Namrata Banerji, Elizabeth Campolongo, Matthew Thompson, Nina Van Tiel, Jackson Miliko, Ed- uardo Bessa, Majid Mirmehdi, Thomas Schmid, Tanya Berger-Wolf, Daniel I.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Babu, Namrata Banerji, Elizabeth Campolongo, Matthew Thompson, Nina Van Tiel, Jackson Miliko, Ed- uardo Bessa, Majid Mirmehdi, Thomas Schmid, Tanya Berger-Wolf, Daniel I

Reference 25

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Observation 1399fdb0-ed67-4347-b94b-45a7a58c720f · outbound

This paper cites LaRue, Heather J.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys LaRue, Heather J

Reference 26

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Observation b076f0a6-9dd9-41b9-b71b-aef87a13739e · outbound

This paper cites Focal loss for dense object detection, 2018.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Focal loss for dense object detection, 2018

Reference 27

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Observation aa93398a-81a4-4919-9050-86a5d961bbd0 · outbound

This paper cites UA V equipped with infrared imaging for Cervi- dae monitoring: Improving detection accuracy by eliminat- ing background information interference.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys UA V equipped with infrared imaging for Cervi- dae monitoring: Improving detection accuracy by eliminat- ing background information interference

Reference 28

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Observation 36371cee-2b04-4e4f-b8a7-59fcc638f772 · outbound

This paper cites An improved bird detection method using surveillance videos from Poyang Lake based on YOLOv8.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys An improved bird detection method using surveillance videos from Poyang Lake based on YOLOv8

Reference 29

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Observation 66344c51-1c2e-4880-9c22-94ca1f5ef418 · outbound

This paper cites Sagar, and David R.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Sagar, and David R

Reference 30

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Observation 6ea09612-1633-482d-b1c3-023889fa03be · outbound

This paper cites Mattern, David M.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Mattern, David M

Reference 31

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Observation 4e501a90-2e46-4cb2-bb15-a3c1df210ad5 · outbound

This paper cites Automated wildlife bird detection from drone footage using computer vision techniques.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Automated wildlife bird detection from drone footage using computer vision techniques

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:07:22.706520Z

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Observation 0958997f-8fa5-4c4d-861f-0b07ef202246 · outbound

This paper cites Drone-based Salvin’s albatross population assessment: feasibility at the Bounty Islands.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Drone-based Salvin’s albatross population assessment: feasibility at the Bounty Islands

Reference 33

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Observation f1bbd607-4208-4347-9e3e-f0358c59c09c · outbound

This paper cites Phillips, R.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Phillips, R

Reference 34

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Observation d45b5632-f9bc-4ee9-bb4a-65f7c48661d9 · outbound

This paper cites Genetic programming with convolutional opera- tors for albatross nest detection from satellite imaging.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Genetic programming with convolutional opera- tors for albatross nest detection from satellite imaging

Reference 35

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Observation 51d4ea9e-9f44-431b-9fe8-c325260aab2d · outbound

This paper cites Benchmarking wild bird detection in complex forest scenes.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Benchmarking wild bird detection in complex forest scenes

Reference 36

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Observation 409cb4dc-197e-45e1-8718-7494dadb8c03 · outbound

This paper cites Salvin’s albatrosses at the Bounty Islands: at-sea dis- tribution.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Salvin’s albatrosses at the Bounty Islands: at-sea dis- tribution

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:07:22.631397Z

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Observation afd514a3-6d11-48cc-8170-1898f5ec0311 · outbound

This paper cites Costelloe, Silvia Zuffi, Benjamin Risse, Alexander Mathis, Mackenzie W.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Costelloe, Silvia Zuffi, Benjamin Risse, Alexander Mathis, Mackenzie W

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:07:22.616863Z

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Observation 4c62629b-b513-46c1-9ced-6f4c8332462e · outbound

This paper cites Weinstein, Sergio Marconi, Stephanie Bohlman, Alina Zare, and Ethan White.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Weinstein, Sergio Marconi, Stephanie Bohlman, Alina Zare, and Ethan White

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:07:22.602237Z

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Observation 2f15506c-4ecc-47c0-bdbd-3a6c6018fa8f · outbound

This paper cites Weinstein, Lindsey Garner, Vienna R.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Weinstein, Lindsey Garner, Vienna R

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:07:22.587316Z

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Observation b2e9742d-c044-4823-a9bd-4f9c0fa9d2b8 · outbound

This paper cites Hughey, Jared A.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Hughey, Jared A

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:07:22.572273Z

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Observation 1f50f36d-e4cb-4b1f-9a03-732398fc7f54 · outbound

This paper cites an unresolved cited work.

Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys Unresolved cited work

Reference 2018

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Pith citing papers

No inbound Pith citation observations are available.