Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:10:17.967967Z
Paper Citation Record · LEDGER
Evolutionary computing-based image segmentation method to detect defects and features in Additive Friction Stir Deposition Process
As of 16 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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
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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.