Paper Citation Record · LEDGER

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n

As of 20 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2607.19535.

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

pith.paper-citation-record.v1
2607.19535 v2

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:30:55.822285Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

33 of 33 outbound references displayed

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verified fuzzy0
unresolved33
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8f3a9aff-38da-4401-8897-cf0f63ef9acc · outbound

This paper cites Artificial intelligence applications in solid waste management: A systematic research review,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Artificial intelligence applications in solid waste management: A systematic research review,

Reference 1

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Observation 0dc20b9d-7e0f-418e-b4de-9083872c83e5 · outbound

This paper cites A survey on image data augmentation for deep learning,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n A survey on image data augmentation for deep learning,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:52.176695Z

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Observation 01857d04-7fbd-4651-b836-bced6f3e1c77 · outbound

This paper cites Cut, paste and learn: Surprisingly easy synthesis for instance detection,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Cut, paste and learn: Surprisingly easy synthesis for instance detection,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:52.278686Z

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Observation 7ca06158-3b94-43ef-8f30-3d00a9ff21f9 · outbound

This paper cites Synthesizing training data for object detection in indoor scenes,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Synthesizing training data for object detection in indoor scenes,

Reference 4

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Observation 17d56cb3-5ef4-4cb9-a713-1db82ee4862e · outbound

This paper cites Simple copy-paste is a strong data augmentation method for instance segmentation,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Simple copy-paste is a strong data augmentation method for instance segmentation,

Reference 5

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Observation 01eeddc8-b35b-49da-9d89-9b2357b565ae · outbound

This paper cites Playing for data: Ground truth from computer games,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Playing for data: Ground truth from computer games,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:52.759938Z

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Observation dd6f71c4-6a6e-4581-a64d-03c86364de10 · outbound

This paper cites The SYNTHIA dataset: A large collection of synthetic images for semantic segmentation of urban scenes,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n The SYNTHIA dataset: A large collection of synthetic images for semantic segmentation of urban scenes,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:52.892091Z

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Observation b17595dd-af32-4b70-bb44-b9f23ec9163f · outbound

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

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Domain randomization for transferring deep neural networks from simulation to the real world,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:53.030661Z

Source-reported events for the cited work

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Observation 903330c1-697c-406d-adc2-6c6ca6171462 · outbound

This paper cites Training deep networks with synthetic data: Bridging the reality gap by domain randomization,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Training deep networks with synthetic data: Bridging the reality gap by domain randomization,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:53.118043Z

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Observation 7fd0e169-7a06-4ed1-a9ed-1fb67c06a2b8 · outbound

This paper cites Contextual priming for object detection,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Contextual priming for object detection,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:53.194498Z

Source-reported events for the cited work

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Observation d2e4b3c9-4ae6-4bd0-ab4d-3df84391d1b1 · outbound

This paper cites An empirical study of context in object detection,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n An empirical study of context in object detection,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:53.290661Z

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Observation c50101c9-714b-4e9a-8ced-ade83f0b526e · outbound

This paper cites The Elephant in the Room.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n The Elephant in the Room

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:53.394899Z

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Observation 99b3458c-e91c-4567-bb08-b82c4031d1f0 · outbound

This paper cites Modeling visual context is key to augmenting object detection datasets,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Modeling visual context is key to augmenting object detection datasets,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:53.451653Z

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Observation d3bc4c6c-9973-479d-967b-1ed16cef9eed · outbound

This paper cites Classification of trash for recyclability status,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Classification of trash for recyclability status,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:53.542778Z

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Observation 30a4c9f0-8367-4bac-b34a-a050642c592d · outbound

This paper cites TACO: Trash Annotations in Context for Litter Detection.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n TACO: Trash Annotations in Context for Litter Detection

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:53.707042Z

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Observation ba1c2598-b530-4e79-bb64-d56677178447 · outbound

This paper cites Hierarchical waste detection with weakly supervised segmentation in images from recycling plants,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Hierarchical waste detection with weakly supervised segmentation in images from recycling plants,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:53.844197Z

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Observation b0e7c4fd-5e1f-4ebc-bf0a-5165431caba3 · outbound

This paper cites ZeroWaste dataset: Towards deformable object segmentation in clut- tered scenes,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n ZeroWaste dataset: Towards deformable object segmentation in clut- tered scenes,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:54.039533Z

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Observation 79416d14-015f-4d27-b11b-f037d698f613 · outbound

This paper cites Garbage detection and classifi- cation using a new deep learning-based machine vision system as a tool for sustainable waste recycling,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Garbage detection and classifi- cation using a new deep learning-based machine vision system as a tool for sustainable waste recycling,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:54.189196Z

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Observation d34b4a9d-50bd-4b3b-966c-6ce7e4753fa7 · outbound

This paper cites Faster R-CNN: Towards real-time object detec- tion with region proposal networks,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Faster R-CNN: Towards real-time object detec- tion with region proposal networks,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:54.322049Z

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Observation f44ce0f4-afbb-4657-9020-1ae8f8dd05f5 · outbound

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

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n You only look once: Unified, real-time object detection,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:54.472054Z

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Observation 3ac2c5d0-6c03-42d7-b362-02755522ecd5 · outbound

This paper cites SSD: Single shot multibox detector,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n SSD: Single shot multibox detector,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:54.643929Z

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Observation 9897c758-5b53-494c-8d96-c6defaf00f17 · outbound

This paper cites MobileNetV2: Inverted residuals and linear bottlenecks,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n MobileNetV2: Inverted residuals and linear bottlenecks,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:54.796504Z

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Observation 786c1005-0f39-45d8-9efd-24d4efb89613 · outbound

This paper cites Ultralytics YOLOv8,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Ultralytics YOLOv8,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:54.899028Z

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Observation 4952f4ab-6015-4d9c-a06c-d7ddfd4c97a8 · outbound

This paper cites Quantization and training of neural networks for efficient integer-arithmetic- only inference,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Quantization and training of neural networks for efficient integer-arithmetic- only inference,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:55.053476Z

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Unavailable: canonical work link unavailable.

Observation a4065591-8a24-412e-b01b-209321754d7d · outbound

This paper cites Quantizing deep convolutional networks for efficient inference: A whitepaper.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Quantizing deep convolutional networks for efficient inference: A whitepaper

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:55.168714Z

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Observation 5ba85c83-4bff-49cb-bab1-9e64c97970db · outbound

This paper cites On pre-trained image features and synthetic images for deep learning,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n On pre-trained image features and synthetic images for deep learning,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:55.259684Z

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Observation ca03ff8f-c568-4cea-adc8-25912717e88e · outbound

This paper cites Approximate statistical tests for comparing supervised classification learning algorithms,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Approximate statistical tests for comparing supervised classification learning algorithms,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:55.328361Z

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Observation 8536e558-86aa-457b-b827-4fc6d14f91a8 · outbound

This paper cites Accounting for variance in machine learning benchmarks,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Accounting for variance in machine learning benchmarks,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:55.389359Z

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Observation dcb2f17e-f69a-42dd-980c-fefce0169d6d · outbound

This paper cites Efron and R.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Efron and R

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:55.492075Z

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Observation eb35636d-df1e-492e-901c-2bc4d924b450 · outbound

This paper cites Microsoft COCO: Common objects in context,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n Microsoft COCO: Common objects in context,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:55.567513Z

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Unavailable: canonical work link unavailable.

Observation 5fa89833-0318-4a67-b8f2-0967088b7519 · outbound

This paper cites The PASCAL visual object classes (VOC) challenge,.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n The PASCAL visual object classes (VOC) challenge,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:55.669218Z

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Observation aefc58fb-1cb6-4bc9-8610-59954e1f8488 · outbound

This paper cites MediaPipe Hands: On-device Real-time Hand Tracking.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n MediaPipe Hands: On-device Real-time Hand Tracking

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:55.752456Z

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Unavailable: canonical work link unavailable.

Observation 172d6f43-25a5-46ad-8e41-6813f9b5f3c2 · outbound

This paper cites How transferable are features in deep neural networks?.

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n How transferable are features in deep neural networks?

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T12:30:55.822285Z

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Pith citing papers

No inbound Pith citation observations are available.