Paper Citation Record · LEDGER

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process

As of 8 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2507.00046.

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

pith.paper-citation-record.v1
2507.00046 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:10:17.967967Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

24 of 24 outbound references displayed

verified exact2
verified fuzzy19
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 599b7ecb-c39c-4ff5-a9f6-c2538f4ebea6 · outbound

This paper cites and Gao, M., 2023.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Gao, M., 2023

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:22.546811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 771f64f5-c02d-4fcf-94c9-4dcc9aad9719 · outbound

This paper cites and Zhang, Q., 2023.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Zhang, Q., 2023

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:22.376785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dcf1f065-3ca2-4aef-8674-de3309dd9b34 · outbound

This paper cites and Szczuko, P., 2023.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Szczuko, P., 2023

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:22.178996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bcc2d600-a684-44c8-ac7f-6921269badb6 · outbound

This paper cites Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T23:10:16.251683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a5b1ee4-3702-4d30-ac0d-c88604c0e33b · outbound

This paper cites U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:10:16.324517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92fe2fd4-2d2f-4f85-8f70-f78755c0bdde · outbound

This paper cites and Chen, D.Z., 2023, October.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Chen, D.Z., 2023, October

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:21.936770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 981579c1-9a51-4cd2-b7a8-9dead23b9e14 · outbound

This paper cites Customized Segment Anything Model for Medical Image Segmentation.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process Customized Segment Anything Model for Medical Image Segmentation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T23:10:16.470557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04137b5a-b5ec-486d-9235-19fed09f0891 · outbound

This paper cites and Fang, Z., 2023.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Fang, Z., 2023

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:21.752496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b05016ce-cc8e-4924-964a-f38cf03c2841 · outbound

This paper cites and Pandey, D., 2023.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Pandey, D., 2023

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:21.506629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 21a629a2-dc6a-4d9a-beb8-d5d399ad7023 · outbound

This paper cites and Guo, M.F., 2023.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Guo, M.F., 2023

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:21.330504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ebb2cf61-b5ca-44cc-8507-e9b5546fe1bf · outbound

This paper cites and Chen, D.Y ., 2023.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Chen, D.Y ., 2023

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:21.048415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 116bc5cf-fc19-42f7-9f44-977f7e6a6558 · outbound

This paper cites and Laddha, S., 2023.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Laddha, S., 2023

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:20.822221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8506e5f3-aea7-4452-95f9-65c5869be0ac · outbound

This paper cites and Alkhazraji, A., 2023.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Alkhazraji, A., 2023

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:20.633978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 47109e5e-02f0-424b-89ce-8d5f660959eb · outbound

This paper cites and du Plessis, A., 2025.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and du Plessis, A., 2025

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:20.392597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2fcedfa7-1479-441a-877f-362770c93f69 · outbound

This paper cites and Reisch, R.T., 2025.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Reisch, R.T., 2025

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:20.172953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 536cecbe-e34f-464a-b9be-d4932e3ff1e6 · outbound

This paper cites and Leung, C.L.A., 2024.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Leung, C.L.A., 2024

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:19.928056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5711e193-3f09-418a-9810-20387f27fe7d · outbound

This paper cites Segmentation of Additive Manufacturing Defects Using U -Net.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process Segmentation of Additive Manufacturing Defects Using U -Net

Reference 17

Resolution: verified exact; doi, observed 2026-08-06T23:10:18.550883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c876e105-6d88-45cd-8b7b-0732e950a7f4 · outbound

This paper cites Evaluation of Image Segmentation Methods for In Situ Quality Assessment in Additive Manufacturing.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process Evaluation of Image Segmentation Methods for In Situ Quality Assessment in Additive Manufacturing

Reference 18

Resolution: verified exact; doi, observed 2026-08-06T23:10:18.243521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5c8ef94d-78c5-48d0-bb36-8ce6470f6747 · outbound

This paper cites and Mishra, R.S., 2024.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Mishra, R.S., 2024

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:19.765951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0529f092-db00-4400-8076-01437a679c9a · outbound

This paper cites and Mishra, R.S., 2024.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Mishra, R.S., 2024

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:19.607216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bca3f3f5-f3a5-4811-960a-748ae4f198fc · outbound

This paper cites and Bhattacharjee, P.P ., 2024.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Bhattacharjee, P.P ., 2024

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:19.424146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d1c4ac4e-c37d-4a4f-a78c-a95df1062b14 · outbound

This paper cites and Paradowska, A.M., 2024.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Paradowska, A.M., 2024

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:19.269945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 32447b8d-b1cd-4702-9025-e331dae4daeb · outbound

This paper cites and Allison, P.G., 2024.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Allison, P.G., 2024

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:19.126535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 92a34c57-4472-4193-94d2-871151aca560 · outbound

This paper cites and Carroll, J., 2022.

Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process and Carroll, J., 2022

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:10:18.845220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.