Paper Citation Record · LEDGER

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study

As of 6 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2509.01769.

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

pith.paper-citation-record.v1
2509.01769 v2

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-18T19:30:58.728694Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T05:01:34.343567Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T05:01:35.755699Z

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy7
unresolved4
parse uncertain3
malformed identifier17
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4e7f68f1-f4f0-4d7b-af3f-2b16cfa8bf56 · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-05-18T19:31:47.739534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 41cc94ea-bb58-4439-90de-6491d7a07860 · outbound

This paper cites [9] specifically for defect detection in additive manufacturing, achieving over 80% accuracy in identifying various defects.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study [9] specifically for defect detection in additive manufacturing, achieving over 80% accuracy in identifying various defects

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:31:47.754901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 47bc30ad-ac78-40c8-8a39-9ae033c430f1 · outbound

This paper cites This section delves into the processes of dataset collection and curation, feature engineering, and selection of ML algorithms.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study This section delves into the processes of dataset collection and curation, feature engineering, and selection of ML algorithms

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:31:47.732700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e8e4a984-b49f-488e-a4c7-6a96b1872938 · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 4

Resolution: parse uncertain; raw_fallback, observed 2026-05-18T19:31:47.743738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a2ce2cb5-98d0-4906-abcb-dd29dbd8fd2c · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-05-18T19:31:47.747887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4da01e26-e7c8-4775-9113-098968514ee2 · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 6

Resolution: parse uncertain; raw_fallback, observed 2026-05-18T19:31:47.741722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 52864ceb-cf25-4f02-8b92-3052c9274429 · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 7

Resolution: parse uncertain; raw_fallback, observed 2026-05-18T19:31:47.728099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 73153379-fccc-46b3-93a9-70f61ff0baea · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-05-18T19:31:47.726070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0d321b06-259c-4601-9631-ec29522bbd3f · outbound

This paper cites Initially, the datasets were collected, cleaned, and prepared by removing illogical data and applying methods like forward, backward, and polynomial filling.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Initially, the datasets were collected, cleaned, and prepared by removing illogical data and applying methods like forward, backward, and polynomial filling

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:31:47.745896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4892a25c-a699-49b9-9ae5-e31ba6ad904e · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-05-18T19:31:47.723692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bea52455-2059-47f3-8a41-115e7551c3b4 · outbound

This paper cites Followed closely were LGBM and XGBoost, with accuracies of 91.08% and 90.89%, respectively.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Followed closely were LGBM and XGBoost, with accuracies of 91.08% and 90.89%, respectively

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:31:47.719410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f5da2343-1719-4aa7-af0e-f965c59ac4c6 · outbound

This paper cites The model exhibited robust performance across different classes, further validating its effectiveness in defect classification tasks.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study The model exhibited robust performance across different classes, further validating its effectiveness in defect classification tasks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:31:47.717165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6290d61e-f185-44f2-8112-8293c43b6dbd · outbound

This paper cites These curves depicted the evolution of model performance with increasing training data, offering insights into model fitting and data requirements.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study These curves depicted the evolution of model performance with increasing training data, offering insights into model fitting and data requirements

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:31:47.721740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bf93fe1f-ac02-4c1b-be36-dbf9edb84d2a · outbound

This paper cites Akbari, F.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Akbari, F

Reference 14

Resolution: malformed identifier; arxiv_id, observed 2026-05-18T19:31:47.011235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation b40cf9ee-be0d-4890-bae1-3e529f0e21a9 · outbound

This paper cites Wang, X.P.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Wang, X.P

Reference 17

Resolution: malformed identifier; arxiv_id, observed 2026-05-18T19:31:47.025408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6ae2758f-0964-4873-b88f-be0f3b61425a · outbound

This paper cites Okaro, S.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Okaro, S

Reference 19

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.709420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation db696e45-135f-4a09-9914-6661bfbd099d · outbound

This paper cites Khanzadeh, S.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Khanzadeh, S

Reference 20

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.712210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fbfc9027-3c63-4f1d-8d52-c60b2a4812ef · outbound

This paper cites Tapia, A.H.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Tapia, A.H

Reference 23

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.706765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 49ed7b5b-83da-453b-a47e-dffc0f5d02de · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 24

Resolution: malformed identifier; arxiv_id, observed 2026-05-18T19:31:47.030265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1b4db3ed-c785-4a81-88a9-d574277d618a · outbound

This paper cites Yuan, Solidification Defects in Additive Manufactured Materials, JOM 71 (2019) 3221–.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Yuan, Solidification Defects in Additive Manufactured Materials, JOM 71 (2019) 3221–

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-18T19:31:47.730442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7c89b754-17df-4c20-8c7b-984de57faea6 · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 26

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.734600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 69c4329d-aac0-48da-a9d2-b8b0e372aea5 · outbound

This paper cites Gaikwad, B.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Gaikwad, B

Reference 27

Resolution: malformed identifier; arxiv_id, observed 2026-05-18T19:31:47.015522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9151adac-b0f0-4107-b66d-ebb40d65d1c4 · outbound

This paper cites Zhang, W.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Zhang, W

Reference 28

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.750147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 26d91696-0f8e-4247-84d7-26adb5454601 · outbound

This paper cites Lecun, Y.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Lecun, Y

Reference 29

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.752527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9d4ce5e1-ee62-4372-bea9-8ff3e14aaac4 · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 30

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.737249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation edac4ee8-94f3-4ab5-9f8f-d9c67ee647cf · outbound

This paper cites Imani, A.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Imani, A

Reference 31

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.700663Z

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Observation c8e8f395-9783-4dd0-bc69-effbef7561ef · outbound

This paper cites Gobert, E.W.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Gobert, E.W

Reference 32

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.703218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 160d9e7c-e0c5-4ae5-afff-39b74153f16e · outbound

This paper cites Scime, J.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Scime, J

Reference 33

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.714582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 84655b30-098e-44b4-88b4-3f9083f4ed79 · outbound

This paper cites Bartlett, A.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Bartlett, A

Reference 34

Resolution: malformed identifier; arxiv_id, observed 2026-05-18T19:31:47.020686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d4b82d75-04fc-4e22-87f9-e3f92fe715d5 · outbound

This paper cites an unresolved cited work.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Unresolved cited work

Reference 35

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.696482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 897ed057-0bdf-443c-a4a1-db2ef7b1d3ba · outbound

This paper cites Kageyama, H.

AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study Kageyama, H

Reference 36

Resolution: malformed identifier; raw_fallback, observed 2026-05-18T19:31:47.698448Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

Observation 1d40dbd5-d3e0-48a4-a266-70ef0ee15bba · inbound

LabelImg: CNN-Based Surface Defect Detection cites this paper.

LabelImg: CNN-Based Surface Defect Detection AM-DefectNet: Additive Manufacturing Defect Classification Using Machine Learning -- A comparative Study

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-05T05:01:35.760394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.