Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:55:17.206707Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 0 inbound Pith citation observations for arXiv:2506.09300.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:55:17.206707Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
6 of 6 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 700b1e57-85cf-4837-a9f3-7847eb003716 · outbound
Efficient Edge Deployment of Quantized YOLOv4-Tiny for Aerial Emergency Object Detection on Raspberry Pi 5 You only look once: Unified, real-time object detection,
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation afccb42e-06cc-4c1b-8a55-558080d8b0f8 · outbound
Efficient Edge Deployment of Quantized YOLOv4-Tiny for Aerial Emergency Object Detection on Raspberry Pi 5 YOLOv4: Optimal Speed and Accuracy of Object Detection
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31187274-44e9-4dbd-bd5c-fce1619482d0 · outbound
Efficient Edge Deployment of Quantized YOLOv4-Tiny for Aerial Emergency Object Detection on Raspberry Pi 5 SSD: Single shot multibox detector,
Reference 3
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 3b9dd624-010a-4845-9c4c-4a2dda3ad7e6 · outbound
Efficient Edge Deployment of Quantized YOLOv4-Tiny for Aerial Emergency Object Detection on Raspberry Pi 5 Ten- sorFlow: A system for large-scale machine learning,
Reference 4
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 1d9aacb5-0d68-41ea-b992-0e0ca63b59ad · outbound
Efficient Edge Deployment of Quantized YOLOv4-Tiny for Aerial Emergency Object Detection on Raspberry Pi 5 Focal loss for dense object detection,
Reference 6
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 ee86aed3-995f-4827-9a48-e0a60d3df4d4 · outbound
Efficient Edge Deployment of Quantized YOLOv4-Tiny for Aerial Emergency Object Detection on Raspberry Pi 5 Benchmarking TinyML Systems: Challenges and Direction
Reference 2020
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.