Tracking Moose using Aerial Object Detection | Paper Citation Record

Observation eef7b88f-5fdf-403c-b754-09e630b32124 · outbound

This paper cites ‘It’s like a connection between all of us’: Inuit social connectio ns and caribou declines in Labrador, Canada,.

Tracking Moose using Aerial Object Detection ‘It’s like a connection between all of us’: Inuit social connectio ns and caribou declines in Labrador, Canada,

Reference 1

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.745550Z

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Observation 901b28d3-a33d-4797-a125-2b83db31aa19 · outbound

This paper cites Vulnerability of Inuit food systems to food i nsecurity as a consequence of cli- mate change: a case study from Igloolik, Nunavut,.

Tracking Moose using Aerial Object Detection Vulnerability of Inuit food systems to food i nsecurity as a consequence of cli- mate change: a case study from Igloolik, Nunavut,

Reference 2

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.734685Z

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Observation 7e897b28-487b-43ea-ba2f-e41ceab832cf · outbound

This paper cites Response of moose to forest ha rvest and management: a literature review,.

Tracking Moose using Aerial Object Detection Response of moose to forest ha rvest and management: a literature review,

Reference 3

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.724416Z

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Observation 469405f6-cb3e-4d93-87ee-2c54470cb142 · outbound

This paper cites A review of methods to estimate and monitor moose density and abundance,.

Tracking Moose using Aerial Object Detection A review of methods to estimate and monitor moose density and abundance,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:29.293125Z

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Observation 9ab9653e-cc28-4c40-9d6c-351d80209cda · outbound

This paper cites A comparison of unmanned aerial vehicles (drones) and manned helicopters for monitoring macropod populations,.

Tracking Moose using Aerial Object Detection A comparison of unmanned aerial vehicles (drones) and manned helicopters for monitoring macropod populations,

Reference 5

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.713728Z

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Observation 5ba04c30-d3c3-4fb5-8dab-59dcfc4c435f · outbound

This paper cites Small-object detection for uav-based images using a distance metric method,.

Tracking Moose using Aerial Object Detection Small-object detection for uav-based images using a distance metric method,

Reference 6

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T13:07:29.283182Z

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Observation 5db132b1-4e53-4278-a587-892564c8076b · outbound

This paper cites Deep learning wor kﬂow to support in-ﬂight processing of digital aerial imagery for wildlife population surveys,.

Tracking Moose using Aerial Object Detection Deep learning wor kﬂow to support in-ﬂight processing of digital aerial imagery for wildlife population surveys,

Reference 7

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.702485Z

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Observation 60c1e4e0-b5b9-41db-8bfa-5a22157fa4e9 · outbound

This paper cites A survey of small object detection bas ed on deep learning in aerial images,.

Tracking Moose using Aerial Object Detection A survey of small object detection bas ed on deep learning in aerial images,

Reference 8

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Observation 389e2deb-e102-48be-a8ac-620cecafd2ae · outbound

This paper cites Small object bird detection in infrared drone videos using mask r- cnn deep learning,.

Tracking Moose using Aerial Object Detection Small object bird detection in infrared drone videos using mask r- cnn deep learning,

Reference 9

Resolution: verified exact; raw_fallback, observed 2026-08-06T13:07:29.183768Z

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Observation 768a375e-6c0f-46ff-b5c4-e067a9aa79a0 · outbound

This paper cites Prescribed grass ﬁre mapping and rate of spread measurement using nir images from a small ﬁxed-wing uas,.

Tracking Moose using Aerial Object Detection Prescribed grass ﬁre mapping and rate of spread measurement using nir images from a small ﬁxed-wing uas,

Reference 10

Resolution: verified exact; raw_fallback, observed 2026-08-06T13:07:29.114823Z

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

Observation c9f37620-52f9-4099-a518-67cbe2c8ead6 · outbound

This paper cites Microsoft COCO: Common Objects in Context.

Tracking Moose using Aerial Object Detection Microsoft COCO: Common Objects in Context

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:26.392951Z

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Observation 4d20381c-e459-49cd-9376-0d860de37276 · outbound

This paper cites The Pascal Visual Object Classes (VOC) Challenge,.

Tracking Moose using Aerial Object Detection The Pascal Visual Object Classes (VOC) Challenge,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:26.396815Z

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Observation f5f27b72-2655-47ac-8768-12ae92d9d325 · outbound

This paper cites Visual tra cking of small animals in cluttered natural environments using a freely moving camera,.

Tracking Moose using Aerial Object Detection Visual tra cking of small animals in cluttered natural environments using a freely moving camera,

Reference 13

Resolution: malformed identifier; no resolver link, observed 2026-08-06T13:07:26.399856Z

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Observation cbbd6386-d4a8-44e9-af2f-d3953058eaac · outbound

This paper cites Wildlife monitoring with drones: A survey of end users,.

Tracking Moose using Aerial Object Detection Wildlife monitoring with drones: A survey of end users,

Reference 14

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.677903Z

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Observation efb94588-4fb0-4f7d-b1c9-8e542e43c412 · outbound

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

Tracking Moose using Aerial Object Detection Au tomated detection of wildlife using drones: Synthesis, opportunities and constraints,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:26.409117Z

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Observation 0432d337-cf8c-449b-9284-989040458fe3 · outbound

This paper cites Ultralytics YOLO,.

Tracking Moose using Aerial Object Detection Ultralytics YOLO,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:29.273756Z

Source-reported events for the cited work

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Observation 9586bd6d-3ec8-4063-83b7-b500f9bb81c8 · outbound

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

Tracking Moose using Aerial Object Detection Faster R-CNN: Tow ards Real-Time Object Detection with Region Proposal Networks,

Reference 18

Resolution: malformed identifier; no resolver link, observed 2026-08-06T13:07:26.414743Z

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Observation 1e6c021b-6307-4336-b2b8-eacb3450c80f · outbound

This paper cites DETRs with Collaborative H ybrid Assignments Training,.

Tracking Moose using Aerial Object Detection DETRs with Collaborative H ybrid Assignments Training,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:29.264146Z

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Observation 9c144938-516f-49c2-a0b1-ff41dda21515 · outbound

This paper cites A new dataset and comparative study for aphid cluster dete ction and segmentation in sorghum ﬁelds,.

Tracking Moose using Aerial Object Detection A new dataset and comparative study for aphid cluster dete ction and segmentation in sorghum ﬁelds,

Reference 20

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.660888Z

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Observation e1ac4434-d73c-4fa1-a1fa-0c76293462b3 · outbound

This paper cites IEEE, 2023.

Tracking Moose using Aerial Object Detection IEEE, 2023

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:26.426385Z

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Observation d20b71de-a988-4bd6-b317-a64e0c87f64b · outbound

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

Tracking Moose using Aerial Object Detection You Only Look Once: Unified, Real-Time Object Detection

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:26.429061Z

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Observation fd7e8e0e-6597-41d1-99c5-2051d4a426e5 · outbound

This paper cites Improvements in Aerial Object Detection: C omparing YOLOv7 with YOLOv5 for Fine Drone and Bird Detection in V olatile Environments,.

Tracking Moose using Aerial Object Detection Improvements in Aerial Object Detection: C omparing YOLOv7 with YOLOv5 for Fine Drone and Bird Detection in V olatile Environments,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:29.253695Z

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Observation bcee3967-363c-4c7c-8e21-aecd8072adef · outbound

This paper cites R ecent Advances for Aerial Object Detection: A Survey,.

Tracking Moose using Aerial Object Detection R ecent Advances for Aerial Object Detection: A Survey,

Reference 24

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.651128Z

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Observation 39a042b8-df42-49d7-9546-c8aa61879399 · outbound

This paper cites Research Towards Y olo-Series Algorithms: Co mparison and Analysis of Object Detection Models for Real-Time UA V Applications,.

Tracking Moose using Aerial Object Detection Research Towards Y olo-Series Algorithms: Co mparison and Analysis of Object Detection Models for Real-Time UA V Applications,

Reference 25

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.641420Z

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Observation 0b4d0810-1e43-4172-bf09-b1ca2f7eb95c · outbound

This paper cites Comparison of YOL O V ersions for Object Detection from Aerial Images,.

Tracking Moose using Aerial Object Detection Comparison of YOL O V ersions for Object Detection from Aerial Images,

Reference 26

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.631421Z

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

Observation c92ba4e8-b42a-43bc-8189-bec953808fee · outbound

This paper cites Efﬁcient-L ightweight YOLO: Improving Small Object Detection in YOLO for Aerial Images,.

Tracking Moose using Aerial Object Detection Efﬁcient-L ightweight YOLO: Improving Small Object Detection in YOLO for Aerial Images,

Reference 27

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.620759Z

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

Observation 2b7f3417-f2d2-41f5-b0a1-6eb2531e901b · outbound

This paper cites Efficient Golf Ball Detection and Tracking Based on Convolutional Neural Networks and Kalman Filter.

Tracking Moose using Aerial Object Detection Efficient Golf Ball Detection and Tracking Based on Convolutional Neural Networks and Kalman Filter

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-06T13:07:27.610191Z

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Observation 599a035c-f8b8-4340-8c51-86878a336654 · outbound

This paper cites YOLO-U A V: Object Detection Method of Unmanned Aerial V ehicle Imagery Based on Efﬁcient Multi- Scale Feature Fusion,.

Tracking Moose using Aerial Object Detection YOLO-U A V: Object Detection Method of Unmanned Aerial V ehicle Imagery Based on Efﬁcient Multi- Scale Feature Fusion,

Reference 29

Resolution: verified exact; raw_fallback, observed 2026-08-06T13:07:28.726729Z

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Observation f8bbe250-0107-442c-818c-a598a6d8a9b2 · outbound

This paper cites MBSDet: A Novel Method for Marin e Object Detection in Aerial Imagery with Complex Background Suppression,.

Tracking Moose using Aerial Object Detection MBSDet: A Novel Method for Marin e Object Detection in Aerial Imagery with Complex Background Suppression,

Reference 30

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.595945Z

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Observation 1f225607-62f5-4574-9cc7-f9a91cc2ef2c · outbound

This paper cites Oriented Bounding Box Representation Based on Continuous Encoding in Oriented SAR Ship Detection,.

Tracking Moose using Aerial Object Detection Oriented Bounding Box Representation Based on Continuous Encoding in Oriented SAR Ship Detection,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:26.478736Z

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Observation 4b02d4ff-ca12-456f-b4e0-bf920e7f1ff6 · outbound

This paper cites Aerial Imaging-Based Soiling Detection System for Solar Photovoltaic Panel Cleanliness Inspectio n,.

Tracking Moose using Aerial Object Detection Aerial Imaging-Based Soiling Detection System for Solar Photovoltaic Panel Cleanliness Inspectio n,

Reference 32

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.585222Z

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Observation 2f018abb-4188-449d-971f-34ca82340409 · outbound

This paper cites CPDD: A Cross-Scenario Pho tovoltaic Defect Detector Based on Fine-Grained Feature Autoencoding and Pseudo-Box Contr astive Learning,.

Tracking Moose using Aerial Object Detection CPDD: A Cross-Scenario Pho tovoltaic Defect Detector Based on Fine-Grained Feature Autoencoding and Pseudo-Box Contr astive Learning,

Reference 33

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T13:07:28.566578Z

Source-reported events for the cited work

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Observation 0055f2d2-cd2a-4896-ab24-efe2f92085ce · outbound

This paper cites Beyond sRGB: Optimizing O bject Detection with Diverse Color Spaces for Precise Wildﬁre Risk Assessment,.

Tracking Moose using Aerial Object Detection Beyond sRGB: Optimizing O bject Detection with Diverse Color Spaces for Precise Wildﬁre Risk Assessment,

Reference 34

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.574025Z

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 d6335608-545f-45c2-9a85-e2a16b445617 · outbound

This paper cites Real-Time Aerial Multispectral O bject Detection with Dynamic Modality-Balanced Pixel-Level Fusion,.

Tracking Moose using Aerial Object Detection Real-Time Aerial Multispectral O bject Detection with Dynamic Modality-Balanced Pixel-Level Fusion,

Reference 35

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.563878Z

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Observation d9094696-ce40-4985-b08d-75020e54eb14 · outbound

This paper cites Mask R-C NN,.

Tracking Moose using Aerial Object Detection Mask R-C NN,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:26.837741Z

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Observation d43be7ac-7c10-4a25-9a44-dfa387c9488d · outbound

This paper cites IEEE, 2019.

Tracking Moose using Aerial Object Detection IEEE, 2019

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:26.874380Z

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Observation f47dc470-3b3d-4d3e-8eee-ef7d90a240e9 · outbound

This paper cites Focal Loss for Dense Object Detection.

Tracking Moose using Aerial Object Detection Focal Loss for Dense Object Detection

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:26.939610Z

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Observation f6873eb5-c709-473d-a886-168ec4070c09 · outbound

This paper cites Multispecies detection and identiﬁcation of African mammals in aerial imagery using convolutional ne ural networks,.

Tracking Moose using Aerial Object Detection Multispecies detection and identiﬁcation of African mammals in aerial imagery using convolutional ne ural networks,

Reference 39

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.544337Z

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

Observation 01653af9-ba4c-4e52-8b8a-0cacaa49b655 · outbound

This paper cites Optimized faster R-CNN for oil wells detection from high-resolution remote s ensing images,.

Tracking Moose using Aerial Object Detection Optimized faster R-CNN for oil wells detection from high-resolution remote s ensing images,

Reference 40

Resolution: malformed identifier; doi_truncated, observed 2026-08-06T13:07:28.402939Z

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Observation b4c51382-659e-4821-8782-d4a5566720b0 · outbound

This paper cites An I mproved Deep Learning Approach for Retrieving Outfalls Into Rivers From UAS Image ry,.

Tracking Moose using Aerial Object Detection An I mproved Deep Learning Approach for Retrieving Outfalls Into Rivers From UAS Image ry,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.230447Z

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Observation 3c85c6f1-dfca-4dc7-9e3c-13876806db8e · outbound

This paper cites Analysis of the performance of Faster R-CNN and YOLOv8 in de tecting ﬁshing vessels and ﬁshes in real time,.

Tracking Moose using Aerial Object Detection Analysis of the performance of Faster R-CNN and YOLOv8 in de tecting ﬁshing vessels and ﬁshes in real time,

Reference 42

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.532649Z

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 45edf5c4-b6ee-4eab-85e0-bf8d023519a5 · outbound

This paper cites Accumulated trivial attention matters in vision transformers on small datasets,.

Tracking Moose using Aerial Object Detection Accumulated trivial attention matters in vision transformers on small datasets,

Reference 43

Resolution: malformed identifier; no resolver link, observed 2026-08-06T13:07:27.400445Z

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Observation 841a32a5-75fb-44ab-9e85-cda3e624f931 · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

Tracking Moose using Aerial Object Detection Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.403936Z

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Observation f0fbf837-1c47-4231-b8cb-fc059fd0881b · outbound

This paper cites Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small Datasets.

Tracking Moose using Aerial Object Detection Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small Datasets

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-06T13:07:28.196046Z

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 5207697c-22aa-4f96-8003-724e3fce0d22 · outbound

This paper cites A Lightweight CNN–Trans former Network With Laplacian Loss for Low-Altitude UA V Imagery Semantic Segmentation,.

Tracking Moose using Aerial Object Detection A Lightweight CNN–Trans former Network With Laplacian Loss for Low-Altitude UA V Imagery Semantic Segmentation,

Reference 46

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T13:07:28.182302Z

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 629f2e32-49d9-4969-b14f-c1687914583e · outbound

This paper cites [Online].

Tracking Moose using Aerial Object Detection [Online]

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:29.243280Z

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 8fd2a0b2-4bf4-45ac-976a-d1920874b4b2 · outbound

This paper cites Dcef 2-yolo: Aerial detection yolo with deformable convolution–efﬁcient feature fusion for small target dete ction,.

Tracking Moose using Aerial Object Detection Dcef 2-yolo: Aerial detection yolo with deformable convolution–efﬁcient feature fusion for small target dete ction,

Reference 48

Resolution: verified exact; doi, observed 2026-08-06T13:07:27.519938Z

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 9df1e16f-bd9e-4001-9c5a-58ca5c1b648d · outbound

This paper cites ESOD: Efficient Small Object Detection on High-Resolution Images.

Tracking Moose using Aerial Object Detection ESOD: Efficient Small Object Detection on High-Resolution Images

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-06T13:07:28.104678Z

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 8929f092-226b-47f6-8348-8736c898e9b6 · outbound

This paper cites D etection and tracking meet drones challenge,.

Tracking Moose using Aerial Object Detection D etection and tracking meet drones challenge,

Reference 50

Resolution: malformed identifier; no resolver link, observed 2026-08-06T13:07:27.423408Z

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Observation 222a12cf-08d8-483b-b2f5-c503e6c96553 · outbound

This paper cites Patch-Level Augmentation for Object Detection in Aerial Images,.

Tracking Moose using Aerial Object Detection Patch-Level Augmentation for Object Detection in Aerial Images,

Reference 51

Resolution: malformed identifier; no resolver link, observed 2026-08-06T13:07:27.426730Z

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Observation 24d4aeb4-3fe9-44ff-be56-ba395e84ee12 · outbound

This paper cites YOLOv11: An Overview of the Key Architectural Enhancements.

Tracking Moose using Aerial Object Detection YOLOv11: An Overview of the Key Architectural Enhancements

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.429798Z

Source-reported events for the cited work

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Observation 83fec947-0cad-4589-8e19-b17bc46d8e86 · outbound

This paper cites moose detect Dataset,.

Tracking Moose using Aerial Object Detection moose detect Dataset,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:29.233516Z

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 2f4cd5f0-0898-40fe-a3c9-61f1db216acc · outbound

This paper cites moose Dataset ,.

Tracking Moose using Aerial Object Detection moose Dataset ,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:29.223586Z

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 6a0c509d-9b94-4673-aa2e-f0ed38322700 · outbound

This paper cites moose Dataset ,.

Tracking Moose using Aerial Object Detection moose Dataset ,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:29.213533Z

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 c1702c88-02d0-41e6-ad94-8437c303fb80 · outbound

This paper cites Moose detection Dataset ,.

Tracking Moose using Aerial Object Detection Moose detection Dataset ,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:29.203180Z

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 80f74b3e-531b-4837-b3dd-7382de0116ff · outbound

This paper cites YOLOv4: Optimal Speed and Accuracy of Object Detection.

Tracking Moose using Aerial Object Detection YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.446178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b735d626-cc0f-4ba8-a279-d4c7b1588433 · outbound

This paper cites YOLO Evolution: A Comprehensive Benchmark and Architectural Review of YOLOv12, YOLO11, and Their Previous Versions.

Tracking Moose using Aerial Object Detection YOLO Evolution: A Comprehensive Benchmark and Architectural Review of YOLOv12, YOLO11, and Their Previous Versions

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.449662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c04b4404-d5a1-48a5-b6f6-d4afa307b462 · outbound

This paper cites Integrating remote sensing and deep le arning into aerial survey of large african mammals,.

Tracking Moose using Aerial Object Detection Integrating remote sensing and deep le arning into aerial survey of large african mammals,

Reference 59

Resolution: verified exact; raw_fallback, observed 2026-08-06T13:07:27.918795Z

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 f88fca8b-909b-4932-922b-79c78faa1d3b · outbound

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

Tracking Moose using Aerial Object Detection End-to-End Object Detection with Transformers

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.457164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 080f3ce8-aad9-46ac-887c-2e7bcca026ec · outbound

This paper cites OpenMMLab Detection Tool box and Benchmark,.

Tracking Moose using Aerial Object Detection OpenMMLab Detection Tool box and Benchmark,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T13:07:29.193381Z

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 fb5dc5b6-0b1a-4bf9-95f8-74f83f5bb677 · outbound

This paper cites Deep Residual Learni ng for Image Recognition,.

Tracking Moose using Aerial Object Detection Deep Residual Learni ng for Image Recognition,

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.464202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9dc13a65-8905-4df3-8949-1b69d8362b68 · outbound

This paper cites ISBN 979835030 7184 pp.

Tracking Moose using Aerial Object Detection ISBN 979835030 7184 pp

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:26.420706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

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