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Paper Citation Record · LEDGER

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery

As of 7 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2507.12727.

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

pith.paper-citation-record.v1
2507.12727 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:44:52.407489Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T16:00:56.890985Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T09:26:02.871000Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact0
  • verified fuzzy20
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c8eb7386-ce85-4c53-8c11-f07674890a59 · outbound

This paper cites From unmanned systems to autonomous intelligent systems,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery From unmanned systems to autonomous intelligent systems,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:55.934347Z

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.

source=pdf_text observed=2026-08-06T16:44:50.334528Z digest=sha256:0e6c5f5034810435c131adec04c4df3b4641982ba9f3ef5fb0abbe1bc23eeaab

Observation 17f5dc10-c11b-4aae-a374-fdcd462bceee · outbound

This paper cites Rich feature hierarchies for accu- rate object detection and semantic segmentation,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery Rich feature hierarchies for accu- rate object detection and semantic segmentation,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:55.811154Z

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.

source=pdf_text observed=2026-08-06T16:44:50.396778Z digest=sha256:64bd41a5fc935738e6a87eceeb29869f719a057e0a259724940ea4b779fbfbdf

Observation 1206b3cf-1a81-49b8-a433-90898af080a5 · outbound

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

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery Microsoft COCO: common objects in context,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:55.656346Z

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.

source=pdf_text observed=2026-08-06T16:44:50.491376Z digest=sha256:36de4c08b75f2ad9345a9f5e6c833354a9546ff14b3a7f46b80e3bffd3c14069

Observation 0df4453a-0a79-413d-9169-1107c87a7f61 · outbound

This paper cites SSD: single shot multibox detector,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery SSD: single shot multibox detector,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:55.464302Z

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.

source=pdf_text observed=2026-08-06T16:44:50.622465Z digest=sha256:0cd7430b5bdbf858fe223b14844ead6896a734b1c1e71bc3268275b820bcc319

Observation 80acf1d0-f6c1-468e-9cb0-1014ae3db6b6 · outbound

This paper cites Faster R-CNN: towards real-time object detection with region proposal networks,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery Faster R-CNN: towards real-time object detection with region proposal networks,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:55.313629Z

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.

source=pdf_text observed=2026-08-06T16:44:50.713795Z digest=sha256:2b3b772c498bfe1b18753baa45e0df811adcd2af7285ca6b889641b447ad5244

Observation 3330df07-e493-4d4c-9936-7ef029b4cf03 · outbound

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

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery You only look once: unified, real-time object detection,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:55.068267Z

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.

source=pdf_text observed=2026-08-06T16:44:50.788365Z digest=sha256:847a4e8c95c6400de013e01d10b714519432a3014923f53fcb3c9424a580505a

Observation 65ef1bfb-7f19-42c0-a246-9439e3f007d1 · outbound

This paper cites YOLO9000: better, faster, stronger,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery YOLO9000: better, faster, stronger,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:54.912105Z

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.

source=pdf_text observed=2026-08-06T16:44:50.863325Z digest=sha256:1bb0a18dd0f4cb74c3502628e35338989f9d3d0f565ad5f8259c63b11371d92f

Observation 90e4f245-e76b-4421-837c-104438fed829 · outbound

This paper cites YOLOv3: An Incremental Improvement.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery YOLOv3: An Incremental Improvement

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T16:44:50.958705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:44:50.958705Z digest=sha256:6441ab25073a955815da27898b8639ec7fd51c4233bdbbd76d56c1df1a66b836

Observation 84248369-a522-45f7-bedc-86e966a0e23c · outbound

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

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T16:44:51.107538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:44:51.107538Z digest=sha256:4934ce4709a1f3cfec79310196f0f3cd791a5dff1b9b79b36e119a80eaade06f

Observation 7ff011dd-84b2-4bfa-865f-1e94e6a9fe06 · outbound

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

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery You only look once: Unified, real-time object detection,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:54.703587Z

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.

source=pdf_text observed=2026-08-06T16:44:51.162062Z digest=sha256:a899f3037271d5b3a4b0bd84333e3a7a91450b37521067335dc6daef24d4f916

Observation 855715d5-598e-4c7e-bcbb-10f9d3d98a25 · outbound

This paper cites YOLOv7: Trainable bag-of- freebies sets new state-of-the-art for real-time object detectors,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery YOLOv7: Trainable bag-of- freebies sets new state-of-the-art for real-time object detectors,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:54.544860Z

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.

source=pdf_text observed=2026-08-06T16:44:51.236165Z digest=sha256:1ef9e5cd0e225d56a80d54144b99fa84649d571daa10b45988900b7bc79e5464

Observation 40df2cea-2ae9-4643-ab3a-13122a5035e6 · outbound

This paper cites YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T16:44:51.317026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:44:51.317026Z digest=sha256:e599e23c2b335249daa757d742c934d624ee1019b4cc4ff90408565604d6fde0

Observation d9f5517a-b8d1-48ab-94bc-03ea7e8b3124 · outbound

This paper cites YOLOv10: Real-Time End-to-End Object Detection.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery YOLOv10: Real-Time End-to-End Object Detection

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T16:44:51.384980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:44:51.384980Z digest=sha256:c3364ead535a2d9acc90e0e01b17448ec1eea991568849816af4b3fd73e72d54

Observation aa228afe-b481-4711-853d-fa55f3723b50 · outbound

This paper cites VisDrone-DET2019: The vision meets drone object detection in im- age challenge results,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery VisDrone-DET2019: The vision meets drone object detection in im- age challenge results,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:54.321606Z

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.

source=pdf_text observed=2026-08-06T16:44:51.456847Z digest=sha256:ef5df6cbe9e285ea82346372395b362058190d4be4bc1e14a4089312c8d1b2e8

Observation 8990748b-bd33-4b83-b066-8a052d022fc5 · outbound

This paper cites ASF-YOLO: A novel YOLO model with attentional scale sequence fusion for cell instance segmentation,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery ASF-YOLO: A novel YOLO model with attentional scale sequence fusion for cell instance segmentation,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:54.174230Z

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.

source=pdf_text observed=2026-08-06T16:44:51.528941Z digest=sha256:3fc142d2618a9b406074c47245c9c2cd1987f0744a63e9b98e5efa249d905306

Observation f159ea26-b35e-4fa2-93c5-09645a1e1bbc · outbound

This paper cites CSPNet: A new backbone that can enhance learning capability of CNN,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery CSPNet: A new backbone that can enhance learning capability of CNN,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:54.028309Z

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.

source=pdf_text observed=2026-08-06T16:44:51.635603Z digest=sha256:f12553955cd03aec9ebd5ccac1a3bbe49f96d435c0a362c3c473d769ca1b89b4

Observation 5c35d71a-7ea3-43f3-aad0-a56582f46692 · outbound

This paper cites EfficientNet: Rethinking model scaling for convolutional neural networks,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery EfficientNet: Rethinking model scaling for convolutional neural networks,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:53.818117Z

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.

source=pdf_text observed=2026-08-06T16:44:51.711889Z digest=sha256:455d02bb4ddbcb1841f3ed953936ff4e96e1a34a15e78ab5621fa64fa600f2e0

Observation 457ed109-34ce-476b-95bb-53be8f2cb1f1 · outbound

This paper cites Soft-NMS: improving object detection with one line of code,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery Soft-NMS: improving object detection with one line of code,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:53.649204Z

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.

source=pdf_text observed=2026-08-06T16:44:51.782066Z digest=sha256:876137e2688f7e47a0987fee0257c2d08a80e13ee4ec88a99a5ed78b2192884c

Observation 300f7a13-633e-42a7-b849-a98e441f044c · outbound

This paper cites Session Peering Provisioning Framework (SPPF),.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery Session Peering Provisioning Framework (SPPF),

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:53.485032Z

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.

source=pdf_text observed=2026-08-06T16:44:51.861882Z digest=sha256:0a0c7bca8b870aa0a91f60964aeeb49ef39704589f8240a26b9c1d1594402bc2

Observation a3b4b574-8162-4f53-b469-9a317faa7565 · outbound

This paper cites EdgeYOLO: An edge-real-time object detector,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery EdgeYOLO: An edge-real-time object detector,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:53.295699Z

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.

source=pdf_text observed=2026-08-06T16:44:51.996049Z digest=sha256:995280d4f7804b9f5999d705a7ff39336c27958b4b05c9dcb28a63ee60d17293

Observation fa06b5b5-ffe9-4a7c-a2bb-1e91a4cf78ff · outbound

This paper cites SSD: Single Shot MultiBox Detector,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery SSD: Single Shot MultiBox Detector,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:53.141337Z

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.

source=pdf_text observed=2026-08-06T16:44:52.111424Z digest=sha256:1d59408238f681ce4a5d570229154313eb000b3715af48375a258c95900d72d4

Observation dcefebbf-7ac3-4279-bdf5-4223fdab5c4f · outbound

This paper cites Object Detection with Deep Learning: A Review.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery Object Detection with Deep Learning: A Review

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T16:44:52.189005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:44:52.189005Z digest=sha256:dbc50df99ec1e3c38437e24d6aa5ec7b2df11d9057ab2f53dd86235ecee739c3

Observation 5445b406-10af-4980-9689-cc27ea04c667 · outbound

This paper cites Perceptual Generative Adversar- ial Networks for Small Object Detection,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery Perceptual Generative Adversar- ial Networks for Small Object Detection,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:52.990550Z

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.

source=pdf_text observed=2026-08-06T16:44:52.269376Z digest=sha256:21e7deea9e25e3e3e940ffd2892c4e045f8be6da5e53b55e1f1a2c5733f5da07

Observation 562e0aa4-b2d6-4dd3-8df8-09083892ad7c · outbound

This paper cites The Unmanned Aerial Vehicle Bench- mark: Object Detection and Tracking,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery The Unmanned Aerial Vehicle Bench- mark: Object Detection and Tracking,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:52.800925Z

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.

source=pdf_text observed=2026-08-06T16:44:52.339564Z digest=sha256:d61d673a45b43491581052bcb2fe40c0542637eed6f61a2e9b79075bb8447a0f

Observation 74b4600c-6858-43a8-93e9-bffff595061f · outbound

This paper cites Efficient Non-Maximum Suppression,.

SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery Efficient Non-Maximum Suppression,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:44:52.632402Z

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.

source=pdf_text observed=2026-08-06T16:44:52.407489Z digest=sha256:bb0ea3019506677bd3c1466adcf05edf64814e5095b9198675a1a1f723d9e54a

Pith citing papers

Observation f56546ac-1c0e-46de-b8ae-73ae05eedb0f · inbound

DroneScan-YOLO: Redundancy-Aware Lightweight Detection for Tiny Objects in UAV Imagery cites this paper.

DroneScan-YOLO: Redundancy-Aware Lightweight Detection for Tiny Objects in UAV Imagery SOD-YOLO: Enhancing YOLO-Based Detection of Small Objects in UAV Imagery

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:26:02.874073Z

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.

source=pdf_text observed=2026-05-10T16:00:56.890985Z digest=sha256:477b929d8adedef7d75ed716022a51c6ab464377bcc6bc0a07df068b31f3b0f3