Paper Citation Record · LEDGER

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps

As of 14 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2411.14467.

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

pith.paper-citation-record.v1
2411.14467 v2

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measured 59 of 59 standing notices

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Reference resolution

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External citation measurements

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Outbound references

Observation c2d7ea54-d822-4b00-a726-9517fb7cd3a8 · outbound

This paper cites an unresolved cited work.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Unresolved cited work

Reference 1

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Observation 1da68ebb-96d8-4c2d-b95f-09479a877def · outbound

This paper cites Theglobalemergence/resurgenceofarboviraldiseasesaspublic health problems.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Theglobalemergence/resurgenceofarboviraldiseasesaspublic health problems

Reference 2

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Observation 3c5609cc-3f33-4d15-9dd0-ef0d3e7c97d6 · outbound

This paper cites Bowler, Konstantin B.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Bowler, Konstantin B

Reference 3

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expression of concern dated 2026-01-22. Source: crossref record 10.1126/science.aee6983->10.1126/science.aax9931:expression_of_concern, observed 2026-07-11T02:55:19.885129+00:00. This notice travels one citation hop only.

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This paper cites Wagner, Eliza M.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Wagner, Eliza M

Reference 4

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This paper cites Hallmann, Martin Sorg, Eelke Jongejans, Henk Siepel, Nick Hofland, Heinz Schwan, Werner Stenmans, Andreas Müller, Hubert Sumser, Thomas Hörren, Dave Goulson, and Hans de Kroon.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Hallmann, Martin Sorg, Eelke Jongejans, Henk Siepel, Nick Hofland, Heinz Schwan, Werner Stenmans, Andreas Müller, Hubert Sumser, Thomas Hörren, Dave Goulson, and Hans de Kroon

Reference 5

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This paper cites Montgomery, Michael W.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Montgomery, Michael W

Reference 6

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Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Unresolved cited work

Reference 7

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This paper cites Han, Kush R.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Han, Kush R

Reference 8

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Observation d74ab002-9d62-48d4-9978-b626f7a974bb · outbound

This paper cites Høye, Johanna Ärje, Kim Bjerge, Oskar L.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Høye, Johanna Ärje, Kim Bjerge, Oskar L

Reference 9

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This paper cites Scaling-up camera traps: monitoring the planet’s biodiversity with networks of remote sensors.Frontiers in Ecology and the Environment, 15(1):26–34, 2017.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Scaling-up camera traps: monitoring the planet’s biodiversity with networks of remote sensors.Frontiers in Ecology and the Environment, 15(1):26–34, 2017

Reference 10

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This paper cites Palmer, Craig Packer, and Jeff Clune.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Palmer, Craig Packer, and Jeff Clune

Reference 11

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This paper cites URL https://www.pnas.org/doi/abs/ 10.1073/pnas.2002545117.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps URL https://www.pnas.org/doi/abs/ 10.1073/pnas.2002545117

Reference 12

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This paper cites Welbourne, Andrew W.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Welbourne, Andrew W

Reference 13

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Observation 70285271-e566-4b20-8933-5ce8cb2cc041 · outbound

This paper cites Hobbs and Cheryl S.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Hobbs and Cheryl S

Reference 14

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Observation 9ced842d-1319-4737-a57c-b4cd75e3ccb4 · outbound

This paper cites Whytock, Jędrzej Świeżewski, Joeri A.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Whytock, Jędrzej Świeżewski, Joeri A

Reference 15

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Observation 826eb06d-4258-4bc6-93fe-a96aa159e04f · outbound

This paper cites Wolff, Brenda Molano-Flores, and Jinelle H.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Wolff, Brenda Molano-Flores, and Jinelle H

Reference 16

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Observation 12f5d0be-7737-461a-b972-84efa7c23659 · outbound

This paper cites Insect pest monitoring with camera-equipped traps: strengths and limitations.Journal of Pest Science, 94(2):203–217, 2021.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Insect pest monitoring with camera-equipped traps: strengths and limitations.Journal of Pest Science, 94(2):203–217, 2021

Reference 17

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This paper cites Ethicalissuesinlethalinsectmonitoring.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Ethicalissuesinlethalinsectmonitoring

Reference 18

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This paper cites Houlihan, Mac Stone, Shawn E.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Houlihan, Mac Stone, Shawn E

Reference 19

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Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Unresolved cited work

Reference 20

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Observation 3ce6fdfd-5495-4e24-b0ac-f7b7a2def14e · outbound

This paper cites Genoud, Gregory M.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Genoud, Gregory M

Reference 21

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This paper cites Bioclip: A vision foundation model for the tree of life.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Bioclip: A vision foundation model for the tree of life

Reference 22

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This paper cites Towards a dynamic vision sensor-based insect camera trap.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Towards a dynamic vision sensor-based insect camera trap

Reference 23

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This paper cites The buz- zometer system: In situ audio recordings of pollinators in flight.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps The buz- zometer system: In situ audio recordings of pollinators in flight

Reference 24

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This paper cites Christopher D.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Christopher D

Reference 25

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This paper cites Smith, and Vincent Deblauwe.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Smith, and Vincent Deblauwe

Reference 26

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Observation abe51ba6-9db7-47db-a166-99af82e2aec4 · outbound

This paper cites Insect-foundation: A foundation model and large-scale 1m dataset for visual insect understanding.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Insect-foundation: A foundation model and large-scale 1m dataset for visual insect understanding

Reference 27

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This paper cites Mann, Toke T.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Mann, Toke T

Reference 28

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This paper cites An automated light trap to moni- tor moths (lepidoptera) using computer vision-based tracking and deep learn- ing.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps An automated light trap to moni- tor moths (lepidoptera) using computer vision-based tracking and deep learn- ing

Reference 29

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Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Unresolved cited work

Reference 30

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This paper cites Insect detect: An open-source diy camera trap for automated insect monitoring.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Insect detect: An open-source diy camera trap for automated insect monitoring

Reference 31

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Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Unresolved cited work

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This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 33

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Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Visual Wake Words Dataset

Reference 34

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This paper cites Tinyml: Tools, applications, challenges, and future research directions.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Tinyml: Tools, applications, challenges, and future research directions

Reference 35

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This paper cites dos Santos, Raimundo Barreto, and Juan G.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps dos Santos, Raimundo Barreto, and Juan G

Reference 36

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This paper cites Object detection of small insects in time-lapse camera recordings.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Object detection of small insects in time-lapse camera recordings

Reference 37

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This paper cites McFarland, David Roy, Toke Thomas Høye, Maxim Larrivée, and David Rolnick.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps McFarland, David Roy, Toke Thomas Høye, Maxim Larrivée, and David Rolnick

Reference 38

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This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 39

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Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Unresolved cited work

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This paper cites The inaturalist species classification and detection dataset.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps The inaturalist species classification and detection dataset

Reference 41

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This paper cites Keras.https://keras.io, 2015.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Keras.https://keras.io, 2015

Reference 42

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Observation 45a9c8ac-19d6-4fa7-9ccd-f40158194932 · outbound

This paper cites Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

Reference 43

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This paper cites Adam: A method for stochastic optimization.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Adam: A method for stochastic optimization

Reference 44

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This paper cites Tensorflow lite micro: Embedded ma- chine learning for tinyml systems.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Tensorflow lite micro: Embedded ma- chine learning for tinyml systems

Reference 45

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Observation 38e532eb-c54e-479e-87ab-a8610ac2912b · outbound

This paper cites Motion vectors and deep neural networks for video camera traps.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Motion vectors and deep neural networks for video camera traps

Reference 46

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Observation d7a50924-d4e1-405d-bfc8-a361e2f16632 · outbound

This paper cites Benchmarking Representation Learning for Natural World Image Collections.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Benchmarking Representation Learning for Natural World Image Collections

Reference 47

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This paper cites Dropout: A simple way to prevent neural networks from over- fitting.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Dropout: A simple way to prevent neural networks from over- fitting

Reference 48

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Observation e2f07f60-e813-4dd3-a59c-13bc33453869 · outbound

This paper cites Interpretable Machine Learning.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Interpretable Machine Learning

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:14.901509Z

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Observation 83f02866-557b-4b19-8491-eece38aec8ab · outbound

This paper cites Enhancing lightweight neural networks for small object detection in iot applications.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Enhancing lightweight neural networks for small object detection in iot applications

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:14.906690Z

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Observation 2accfe90-169e-4d53-bff5-aa7d6e7343ed · outbound

This paper cites A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:14.913510Z

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Observation 38a27321-f3d7-48ef-a4ec-e0ceed5d3b1f · outbound

This paper cites Mandrekar.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Mandrekar

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:14.889726Z

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Observation 942b079a-89d3-4dc6-a7e2-28890ad4ee4a · outbound

This paper cites Taylor, and Stefan C.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Taylor, and Stefan C

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:14.895429Z

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Observation 57265e5e-5f7a-48a6-8d37-b44878875d36 · outbound

This paper cites User-based design specifications for the ultimate camera trap for wildlife research.Wildlife Research, 39(8):649–660, 2012.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps User-based design specifications for the ultimate camera trap for wildlife research.Wildlife Research, 39(8):649–660, 2012

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:19:16.095308Z

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

Observation bfa38abb-3ebd-42c2-9e79-7ba50b025ef1 · outbound

This paper cites Snapshot serengeti, high-frequency annotated camera trap images of 40 mammalian species in an african savanna.Scientific Data, 2(1):150026, Jun 2015.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps Snapshot serengeti, high-frequency annotated camera trap images of 40 mammalian species in an african savanna.Scientific Data, 2(1):150026, Jun 2015

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:14.926450Z

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Observation b541f564-45bf-4b91-abf9-a20758e2024c · outbound

This paper cites URL https://www.pnas.org/doi/abs/ 10.1073/pnas.2023989118.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps URL https://www.pnas.org/doi/abs/ 10.1073/pnas.2023989118

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:14.649186Z

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Observation 7c17b0a7-25d6-41e7-b5c6-7d7246304bcb · outbound

This paper cites URL https://www.pnas.org/doi/abs/ 10.1073/pnas.2220283120.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps URL https://www.pnas.org/doi/abs/ 10.1073/pnas.2220283120

Reference 2023

Resolution: verified exact; doi, observed 2026-08-12T18:19:15.351144Z

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Observation 447ef595-d122-41b0-b4bf-57f3bf502808 · outbound

This paper cites URL https://www.

Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps URL https://www

Reference 9541

Resolution: unresolved; no resolver link, observed 2026-08-12T18:19:14.884354Z

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Pith citing papers

Observation df127bab-a012-4050-84a4-c71a3f1cf3c0 · inbound

EV-Flying: an Event-based Dataset for In-The-Wild Recognition of Flying Objects cites this paper.

EV-Flying: an Event-based Dataset for In-The-Wild Recognition of Flying Objects Towards Scalable Insect Monitoring: Ultra-Lightweight CNNs as On-Device Triggers for Insect Camera Traps

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:52:50.142562Z

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