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Paper Citation Record · LEDGER

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images

As of 13 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2411.11738.

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

pith.paper-citation-record.v1
2411.11738 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:15:18.133222Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

53 of 53 outbound references displayed

  • verified exact6
  • verified fuzzy11
  • unresolved36
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1a6fa4f9-6ebc-411b-989b-428773b50802 · outbound

This paper cites an unresolved cited work.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Unresolved cited work

Reference 1

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unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.609194Z digest=sha256:4513db31ffd8908fdf20b1acb7569875de24e0a9b1224ed0589e5074c8021ea7

Observation 62002477-33f1-43f6-8536-672a9d488bd9 · outbound

This paper cites A review of recent application of near infrared spectroscopy to wood science and technology.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images A review of recent application of near infrared spectroscopy to wood science and technology

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.468829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.616909Z digest=sha256:5b46b68bcb308a6b48d766be98428863b60e2ff7baae41b483e0d1106d2ea26b

Observation caffc8bb-ecd3-48ed-9b7c-7d96e032329a · outbound

This paper cites Overview of current practices in data analysis for wood identification-a guide for the different timber tracking methods, 2020.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Overview of current practices in data analysis for wood identification-a guide for the different timber tracking methods, 2020

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.437480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.636118Z digest=sha256:ef4471499dc7a252a0de76a918ddfd35ac3227191534d4c142a7ac18a74cc599

Observation ef2a4da1-d8d5-4095-86f0-c35dc67d4d3b · outbound

This paper cites Flaig, Jens Berger, Philip Wenig, Andrea Olbrich, and Bodo Saake.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Flaig, Jens Berger, Philip Wenig, Andrea Olbrich, and Bodo Saake

Reference 4

Resolution
verified exact
doi, observed 2026-08-12T18:15:18.408544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.644303Z digest=sha256:17fc5b11fb603a36142e864c69c58800f08ffd830d007765c653a41157875b32

Observation 9bf459c0-b749-4a86-a7d1-ac1c6aa6cc0d · outbound

This paper cites Atlas of vessel elements: Identification of asian timbers.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Atlas of vessel elements: Identification of asian timbers

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.401222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.651721Z digest=sha256:e5bffca11b19556c24549d5046831fb6e62f646e3a697f3cb38623ff2bd1ea53

Observation 4a683842-9265-4984-9826-f964d1631e97 · outbound

This paper cites Fiber atlas: identification of papermaking fibers.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Fiber atlas: identification of papermaking fibers

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.367419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.657817Z digest=sha256:94d9f4a1d3cda3302e24d2c085cc18f08d57fa24cbdbe50b7dfa938b39bf7da6

Observation 38af6755-2e19-4c8a-a6fb-30abc8243988 · outbound

This paper cites Atlas of macroscopic wood identification: with a special focus on timbers used in Europe and CITES-listed species.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Atlas of macroscopic wood identification: with a special focus on timbers used in Europe and CITES-listed species

Reference 7

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verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.339176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.668135Z digest=sha256:520d39bd34d250bda8990dbe1da9524ced5edf6c61f43047c1f54e57164527e4

Observation 9a36afa1-2244-4408-8a7a-f696ab821ff5 · outbound

This paper cites Computer vision-based wood identification: A review.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Computer vision-based wood identification: A review

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.292821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.677013Z digest=sha256:b4eb5ab9698a91d35d31001391921232a89c2a0a4d66f1f701ed8bfcc3e03836

Observation e26dcee5-addf-45b0-9601-82be5abb3396 · outbound

This paper cites Mywood-premium, 2018.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Mywood-premium, 2018

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.258136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.684581Z digest=sha256:d263f6aaac592f97c93f0e41fdd374dc0e7ef0e9d3f14a05b9fe5d5ba2b5268b

Observation ca4bb269-3266-4ef4-84c8-2f3def454cfe · outbound

This paper cites The xylotron: flexible, open-source, image-based macroscopic field identification of wood products.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images The xylotron: flexible, open-source, image-based macroscopic field identification of wood products

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.212731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.693628Z digest=sha256:220bb4e362a11f8b1d3d1a0259e00bdee552fab1240ed009064cdee44e610d00

Observation f3f1a127-263a-4eba-ad52-6ce48896b1db · outbound

This paper cites The xylophone: toward democratizing access to high-quality macroscopic imaging for wood and other substrates.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images The xylophone: toward democratizing access to high-quality macroscopic imaging for wood and other substrates

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.132056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.703795Z digest=sha256:a673a409d93faa7507e4451492042c8ea56cbcdb5a1401e07ca70764366ac324

Observation ad72bf7c-ae14-440e-8251-2d55d2520625 · outbound

This paper cites Automating wood species detection and classification in microscopic images of fibrous materials with deep learning, 2023.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Automating wood species detection and classification in microscopic images of fibrous materials with deep learning, 2023

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.091233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.711724Z digest=sha256:d0e3bc92e2e46c196bbb074f5c31992814fc211ce72705fd5c8d24394f7a599f

Observation b8a71f01-29af-4b38-be00-e087d225aa7b · outbound

This paper cites Microsoft COCO: Common Objects in Context.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Microsoft COCO: Common Objects in Context

Reference 13

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unresolved
no resolver link, observed 2026-08-12T18:15:17.721344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.721344Z digest=sha256:8285ec13bbe13468b1a79f7184a584d0e9d2ff3680554f82726af5cd0a2c23de

Observation 6058e245-dabb-4413-8088-347e51257d65 · outbound

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

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Reference 14

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unresolved
no resolver link, observed 2026-08-12T18:15:17.731211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.731211Z digest=sha256:a6ce2320c8d46aab5a5c8f58135bd2d2655b550c94e6140514da91eb098472d2

Observation 67da1013-de6b-4357-8873-1d1d83d596f8 · outbound

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

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images End-to-End Object Detection with Transformers

Reference 15

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no resolver link, observed 2026-08-12T18:15:17.738806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.738806Z digest=sha256:b702aa774f9e4a601761e64c45b4955417ae25908719762baa93093456d9ec41

Observation 6a8f4582-af06-4202-9503-2474c2239511 · outbound

This paper cites DETRs Beat YOLOs on Real-time Object Detection.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images DETRs Beat YOLOs on Real-time Object Detection

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:17.746045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.746045Z digest=sha256:4a79d6c48df1449282a9d9242b67eafee8b1ac6548b5c201d69fbdd62e784f59

Observation 52dff048-2522-41cd-85f1-a36f786901a2 · outbound

This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:17.767121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.767121Z digest=sha256:80907d6714614e5cb8aa00606c398e7e50470ab0664da451f1b8469045d7333d

Observation 4e7ed2bb-b394-4604-aebc-a8610319752c · outbound

This paper cites NMS Strikes Back.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images NMS Strikes Back

Reference 18

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no resolver link, observed 2026-08-12T18:15:17.776122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.776122Z digest=sha256:18907c5df3cdc389ee124a9b8e21375980f6e5db49a0d6b7b45d3238ee96b94b

Observation ef3e9f49-264b-4fe4-a70e-b3efb8efcd9a · outbound

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

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images You Only Look Once: Unified, Real-Time Object Detection

Reference 19

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no resolver link, observed 2026-08-12T18:15:17.789957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.789957Z digest=sha256:79170071e774d90a00bb980a87ff12b34d370703378074855001eb2940e9c68e

Observation 0dfad357-b2e7-4318-aa23-d930c90bd02f · outbound

This paper cites YOLO9000: Better, Faster, Stronger.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images YOLO9000: Better, Faster, Stronger

Reference 20

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no resolver link, observed 2026-08-12T18:15:17.799470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.799470Z digest=sha256:9248c077aa2bc03ea9bd125ec97e6ae7bfaeca939daa758f3ee1d0d1554d57dc

Observation 4c666585-705a-42f5-80b1-07eb1c98ed35 · outbound

This paper cites YOLOv3: An Incremental Improvement.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images YOLOv3: An Incremental Improvement

Reference 21

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no resolver link, observed 2026-08-12T18:15:17.815173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.815173Z digest=sha256:36beb5a1bbc4745e0640c99edccb6ec604daacfd1ee1aac0b09e0ee47c571db7

Observation ed679d7c-6af1-4b2b-a3b4-72d85f52851a · outbound

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

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 22

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no resolver link, observed 2026-08-12T18:15:17.824075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.824075Z digest=sha256:7e55fa2cfd27c160f8f1f14830f2db7c7787cf6320d735ff3943eedcad3a8fcb

Observation a730ec9d-3c79-42df-9895-2efb22a05768 · outbound

This paper cites Scaled-YOLOv4: Scaling Cross Stage Partial Network.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Scaled-YOLOv4: Scaling Cross Stage Partial Network

Reference 23

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unresolved
no resolver link, observed 2026-08-12T18:15:17.838477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.838477Z digest=sha256:0ffe880656e392e37e7fffd2ce32d15e0c75f7723bff4e5efcdfe47ddb1626f7

Observation 8ceb8d84-8f6f-48ab-954f-72dfa77f6a4c · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images YOLOX: Exceeding YOLO Series in 2021

Reference 24

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no resolver link, observed 2026-08-12T18:15:17.846988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.846988Z digest=sha256:b809d8b31d4301ccd4ab6ec4e6a1a1c8b54956fa25f57871542a632ccb0b0f49

Observation 19e5ddb9-8bcc-4ffd-94f8-d10a1611add2 · outbound

This paper cites YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

Reference 25

Resolution
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no resolver link, observed 2026-08-12T18:15:17.857273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.857273Z digest=sha256:32417ccf6bec1a388b82e8809a25ab9df4df1abdd4873a6b610fd3d76c1710f4

Observation fb40b786-e672-473f-8120-e394ab8cdfcb · outbound

This paper cites DAMO-YOLO : A Report on Real-Time Object Detection Design.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images DAMO-YOLO : A Report on Real-Time Object Detection Design

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:17.869841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.869841Z digest=sha256:e68a131f029cbb35d14096c7f459fdd95e228cc5dd2436d7e7057769b952e54e

Observation ce7a56d4-3943-4e9b-88e2-f999651a5348 · outbound

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

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

Reference 27

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unresolved
no resolver link, observed 2026-08-12T18:15:17.884101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.884101Z digest=sha256:72961734169999aecdcc127fea5d48c1782479dc7385e4cade80b928b4d8e94e

Observation 926bbb1f-25e2-4139-847b-749e58ba48ef · outbound

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

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images YOLOv10: Real-Time End-to-End Object Detection

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:17.892295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.892295Z digest=sha256:8405d362925a1d3b5b6b3bc92cb2bf0eee7ff65fcd67296340a499ab598114fe

Observation 6eb79c91-8598-4467-9f87-502d1ac17402 · outbound

This paper cites PP-YOLO: An Effective and Efficient Implementation of Object Detector.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images PP-YOLO: An Effective and Efficient Implementation of Object Detector

Reference 29

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unresolved
no resolver link, observed 2026-08-12T18:15:17.905320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.905320Z digest=sha256:e5c7b6bf0f445a23841ec469d969fef8494d107876570cde1fb6a5f3481651f3

Observation 1b397c34-ab71-473e-9ec8-27e2de978208 · outbound

This paper cites PP-YOLOv2: A Practical Object Detector.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images PP-YOLOv2: A Practical Object Detector

Reference 30

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no resolver link, observed 2026-08-12T18:15:17.913977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.913977Z digest=sha256:3c21b90c53046ac375e72e2f04e092744f4edb1809a031ed36398bf31de16cd1

Observation dac5d703-5894-4986-abcd-f2a0797c572f · outbound

This paper cites PP-YOLOE: An evolved version of YOLO.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images PP-YOLOE: An evolved version of YOLO

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:17.921931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.921931Z digest=sha256:c0537ccc754c78bb0f8dfd1d4947f747f56bee395828c58e8be54dfd18129e93

Observation fb63af48-b87c-4e2e-a541-c68aba22f822 · outbound

This paper cites Segmentation and characterization of macerated fibers and vessels using deep learning.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Segmentation and characterization of macerated fibers and vessels using deep learning

Reference 32

Resolution
verified exact
doi, observed 2026-08-12T18:15:18.365012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.927949Z digest=sha256:5c1eb23298a63a9589d441d633ba030746ebf69a6c4d3fc680cbde63584239ae

Observation e0da290d-3a2d-48d4-9d4d-2a2225a0eea5 · outbound

This paper cites Automatic cell counting with yolov5: A fluorescence microscopy approach.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Automatic cell counting with yolov5: A fluorescence microscopy approach

Reference 33

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verified exact
doi, observed 2026-08-12T18:15:18.330069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.936119Z digest=sha256:e5fca3c71b3d5b745479bc1459cf37cdd5248c232d8d60d03cf3a61521d457d1

Observation fc9f86bf-8268-44d4-9a64-a1d9ab9552ee · outbound

This paper cites an unresolved cited work.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Unresolved cited work

Reference 34

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verified exact
doi, observed 2026-08-12T18:15:18.281327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.943906Z digest=sha256:5a21e9d6a1761e948d03d6648e21787464750bd293dd7d83cd80fd74f35122f6

Observation 54381def-99b3-4cd1-8c03-193f1fd0ed3c · outbound

This paper cites Yolov7-ma: Improved yolov7-based wheat head detection and counting.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Yolov7-ma: Improved yolov7-based wheat head detection and counting

Reference 35

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verified exact
doi, observed 2026-08-12T18:15:18.240304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.952482Z digest=sha256:0553d5e3d9f1d644c180736fcf8a0c839046b72eac30d1f100c23830a29a35a0

Observation 5decebfd-14df-4dae-b54d-34d0a45a20bd · outbound

This paper cites Semo-yolo: A multiscale object detection network in satellite remote sensing images.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Semo-yolo: A multiscale object detection network in satellite remote sensing images

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:17.964792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.964792Z digest=sha256:b1778f5b0f1103d4d1c81cf2eac7a8b0b6be631f91003c8ef3adf008f2d62ed0

Observation 4eb6cdc0-a7fa-45b9-854b-0c20672fc95f · outbound

This paper cites Preparation of thin sections of synthetic resins and wood-resin composites, and a new macerating method for wood.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Preparation of thin sections of synthetic resins and wood-resin composites, and a new macerating method for wood

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:15:20.054932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.973033Z digest=sha256:72c05eb67147aacfd68814f3dd85ffca0eab07be483c4fe3fec1107cdcee5c46

Observation e47c7312-aadb-4a08-bf43-08a53ae095b9 · outbound

This paper cites an unresolved cited work.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-12T18:15:20.023299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:17.980050Z digest=sha256:f6a876c6c77ea39f98469f6782a859db6eff628f14e177a58bf7cdb3642d7443

Observation 940645bf-1544-4f54-8607-2ea0d3f222a5 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 39

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unresolved
no resolver link, observed 2026-08-12T18:15:17.986932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.986932Z digest=sha256:686e2c64f8849c33672abed65d78c1fe257984cd98d7d5575cca8d3042bcb50c

Observation a393d440-f6ca-4024-a3da-cc73ec7590a0 · outbound

This paper cites A ConvNet for the 2020s.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images A ConvNet for the 2020s

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:17.997983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:17.997983Z digest=sha256:213e2c4217a716ce0e16e2132e4f3d298971637a65434eaef5d08c3c2025b104

Observation 572e99a4-358c-45c6-8b50-6ebc1a5149ad · outbound

This paper cites Deep Residual Learning for Image Recognition.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Deep Residual Learning for Image Recognition

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:18.006013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.006013Z digest=sha256:a693cc83e470b78b2e828a41f9a6680c1290aa8c048b35f4973668c50e64d2ec

Observation 17f037b0-343f-46e4-88ed-28707aa4b40d · outbound

This paper cites CSPNet: A New Backbone that can Enhance Learning Capability of CNN.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images CSPNet: A New Backbone that can Enhance Learning Capability of CNN

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:18.014679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.014679Z digest=sha256:7695a37cfa24e142713f0405cd638e2c54d9091edddfe57a7cf06acaa352a789

Observation 5ca5539d-7ccf-49a3-814c-55d3041c5bdc · outbound

This paper cites Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:18.036449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.036449Z digest=sha256:0ead1ecc0231528cdaacfc39923d3f64c7dc1783c19607a20d840594ef1aebcf

Observation 13aa5a5f-4152-4650-869b-730215208355 · outbound

This paper cites Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:18.045115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.045115Z digest=sha256:34386c5ed975b19f700b2417e13c31f8e22f9e242df1982c0e8a54bce877997c

Observation 8fe2a209-6ec6-4cd2-b790-245befade354 · outbound

This paper cites Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:18.057478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.057478Z digest=sha256:5a8cfc82de16cdba5fd01348c899e4b82a2cda5ef8a1bf54e0c708006835c3f4

Observation 5c94dcea-0477-4bce-af9e-17ca558f1cdb · outbound

This paper cites Williams, John Winn, and Andrew Zisserman.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Williams, John Winn, and Andrew Zisserman

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:18.064790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.064790Z digest=sha256:f2e0298de4b08f6737b4b117e6dba4ef5deb369f9f4ce6797da82ea532063101

Observation 1915f9fe-01f1-40ca-a6c8-77fc86ffbabd · outbound

This paper cites FCOS: Fully Convolutional One-Stage Object Detection.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images FCOS: Fully Convolutional One-Stage Object Detection

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:18.077127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.077127Z digest=sha256:12a49fcd1867472c44703e0acf9f399dfbcff70b3979c1e86a42b7e2141ec0c9

Observation f2bcdb72-069d-4b6b-8ef9-1b63a7178754 · outbound

This paper cites OTA: Optimal Transport Assignment for Object Detection.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images OTA: Optimal Transport Assignment for Object Detection

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-12T18:15:18.732002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-08-12T18:15:18.085347Z digest=sha256:35dc784c29e5ee41e8f55f0c972f2b097fa595edd11f47ef9b5553c83aaee7e4

Observation e1fda0bb-20f2-412a-91e1-8488a9d972e6 · outbound

This paper cites TOOD: Task-aligned One-stage Object Detection.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images TOOD: Task-aligned One-stage Object Detection

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:18.092486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.092486Z digest=sha256:ab6dfd8c952c665456a8ff1187f587cc6c0eaf24678057118174ffa3bc76a670

Observation a7b99e84-f3be-4a93-bd53-c5198d04a038 · outbound

This paper cites RepVGG: Making VGG-style ConvNets Great Again.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images RepVGG: Making VGG-style ConvNets Great Again

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:18.104135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.104135Z digest=sha256:934c90ca4bd9227a588ef487d8988872372bcc9de4f83e96eb2ee85c6d8e8c30

Observation 20c02315-8081-43c6-b50e-4c4da4396a19 · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T18:15:18.116589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.116589Z digest=sha256:66356d668d7c0cd306d53ab87e997c84a721b607c132032f0d5d76edb7ba4a97

Observation 472f2207-1c50-471d-bf34-2fa080d9be0d · outbound

This paper cites Squeeze-and-Excitation Networks.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Squeeze-and-Excitation Networks

Reference 52

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unresolved
no resolver link, observed 2026-08-12T18:15:18.126523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.126523Z digest=sha256:b0c0b068de5f7107b9293048eae616fb4849b2076124a7f4bc335c35913b98f6

Observation c5ff36a2-3f32-4e0d-8dbf-e9e748d39baa · outbound

This paper cites Bag of Tricks for Image Classification with Convolutional Neural Networks.

WoodYOLO: A Novel Object Detector for Wood Species Detection in Microscopic Images Bag of Tricks for Image Classification with Convolutional Neural Networks

Reference 53

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unresolved
no resolver link, observed 2026-08-12T18:15:18.133222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T18:15:18.133222Z digest=sha256:feac4013f408bbd1aed092ea5ee5e34e37dd2bc38cf8273e8e25061241456456

Pith citing papers

No inbound Pith citation observations are available.