Paper Citation Record · LEDGER

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network

As of 19 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2411.11029.

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

pith.paper-citation-record.v1
2411.11029 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:07:07.160472Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:45:02.319240Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T00:45:02.594623Z

Reference resolution

37 of 37 outbound references displayed

verified exact0
verified fuzzy35
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c3449482-cacb-41a0-8ad3-0952889d93b1 · outbound

This paper cites In: 2023 IEEE Inter- national Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), pp.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network In: 2023 IEEE Inter- national Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), pp

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.875538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dbb42e71-269d-4ea8-b1a0-3bf9c5307050 · outbound

This paper cites In: 38th European Mask and Lithography Conference (EMLC 2023), vol.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network In: 38th European Mask and Lithography Conference (EMLC 2023), vol

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.844979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0031f8fc-1ea0-4e11-a7e2-43f8baa1746d · outbound

This paper cites Physical Review B 99(4), 041405 (2019).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Physical Review B 99(4), 041405 (2019)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.818614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 30af1b31-f328-45aa-afb3-e9c95b119538 · outbound

This paper cites Journal of photochemistry and photobiology A: Chemistry 108(1), 1–35 (1997).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Journal of photochemistry and photobiology A: Chemistry 108(1), 1–35 (1997)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.799630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bf699696-eb5e-408f-a751-ef79ab81982c · outbound

This paper cites Computers & Industrial Engineering 166, 107977 (2022).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Computers & Industrial Engineering 166, 107977 (2022)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.782838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 254c6886-e5ba-4b70-8b8d-93732eb08167 · outbound

This paper cites In: 20th International Symposium on Quality Electronic Design (ISQED), pp.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network In: 20th International Symposium on Quality Electronic Design (ISQED), pp

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.766062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3797d3c4-9147-4d65-b9be-af1361b68916 · outbound

This paper cites In: Koren, I.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network In: Koren, I

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.749022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 47d65ff7-cb57-48f7-84af-6933cf58d910 · outbound

This paper cites Journal of electronic testing 37, 427–437 (2021).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Journal of electronic testing 37, 427–437 (2021)

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.729827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b9b4fdd0-fd85-4b87-9343-0d143af075bb · outbound

This paper cites IEEE Transactions on Semiconductor Manufacturing 34(3), 365–371 (2021).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network IEEE Transactions on Semiconductor Manufacturing 34(3), 365–371 (2021)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.713686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 07023309-cc09-43fb-b43f-66f933d844a9 · outbound

This paper cites In: 2019 International Conference on Engineering and Telecommunication (EnT), pp.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network In: 2019 International Conference on Engineering and Telecommunication (EnT), pp

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.696138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 122ef5a9-8134-4626-bcd9-0925ea365e2d · outbound

This paper cites Expert Systems with Applications 233, 120923 (2023).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Expert Systems with Applications 233, 120923 (2023)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.679621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 98817995-888d-49b9-a985-b8e0d13d513a · outbound

This paper cites Microelectronics Reliability 38(6-8), 1155–1164 (1998).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Microelectronics Reliability 38(6-8), 1155–1164 (1998)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.662649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1572e9bc-4797-4c18-9e06-b4ea6e1e5eb7 · outbound

This paper cites IEEE Transactions on Semiconductor Manufacturing 28(3), 431–437 (2015).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network IEEE Transactions on Semiconductor Manufacturing 28(3), 431–437 (2015)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.644768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fc9a8527-cfbe-49a4-8c6d-61ec3c4e798b · outbound

This paper cites IEEE Transactions on Semiconductor Manufacturing 31(1), 156–165 (2017).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network IEEE Transactions on Semiconductor Manufacturing 31(1), 156–165 (2017)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.626232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0a9b6122-6d37-4870-8a01-2ea19d34373d · outbound

This paper cites IEEE transactions on computer-aided design of integrated circuits and systems 37(4), 832–844 (2017).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network IEEE transactions on computer-aided design of integrated circuits and systems 37(4), 832–844 (2017)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.606041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 16a2db04-4c82-4bcd-a239-61b7f7b8242c · outbound

This paper cites In: Proceedings of the 28th Asia and South Pacific Design Automation Conference, pp.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network In: Proceedings of the 28th Asia and South Pacific Design Automation Conference, pp

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.587856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fedcd9da-04b6-4ae2-8734-5ba379ea20cf · outbound

This paper cites IEEE Transactions on Semiconduc- tor Manufacturing 31(2), 309–314 (2018).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network IEEE Transactions on Semiconduc- tor Manufacturing 31(2), 309–314 (2018)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.571388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ca48215a-bf16-43b5-825f-cee1813c3625 · outbound

This paper cites Journal of Intelligent Manufacturing 34(8), 3599–3621 (2023) 24.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Journal of Intelligent Manufacturing 34(8), 3599–3621 (2023) 24

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.553014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 20bd30a6-e684-412f-8d5a-972fa7fa330c · outbound

This paper cites In: 2013 IEEE International Test Conference (ITC), pp.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network In: 2013 IEEE International Test Conference (ITC), pp

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.535807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 810627d4-8c28-4dfa-9410-a409f487e8b2 · outbound

This paper cites IEEE Intelligent Systems and their applications 13(4), 18–28 (1998).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network IEEE Intelligent Systems and their applications 13(4), 18–28 (1998)

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T19:07:07.072177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1277fc1e-3169-4234-88d8-0b0c3d5eb624 · outbound

This paper cites Scholarpedia 4(2), 1883 (2009).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Scholarpedia 4(2), 1883 (2009)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.505077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d312529e-1848-4ffa-8e42-d1374a88a751 · outbound

This paper cites Wiley Interdisciplinary Reviews: Computational Statistics 5(6), 448–455 (2013).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Wiley Interdisciplinary Reviews: Computational Statistics 5(6), 448–455 (2013)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.486844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3db94083-da4f-4734-978b-4142a51dd3f7 · outbound

This paper cites IEEE Transactions on Semiconductor Manufacturing 28(1), 1–12 (2014).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network IEEE Transactions on Semiconductor Manufacturing 28(1), 1–12 (2014)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.470029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3f19ebca-3e2c-4950-a15b-a0540ea4be65 · outbound

This paper cites An Evaluation of Large Language Models in Bioinformatics Research.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network An Evaluation of Large Language Models in Bioinformatics Research

Reference 24

Resolution: metadata mismatch; local_arxiv, observed 2026-08-12T19:07:07.208593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7365d2d7-9273-4174-98d3-ecbce189b1ad · outbound

This paper cites GigaScience 13, 018 (2024).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network GigaScience 13, 018 (2024)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.453449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4775d3da-b422-4064-b8be-94bcfad8abad · outbound

This paper cites Quality and Reliability Engineering International 36(4), 1245– 1257 (2020).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Quality and Reliability Engineering International 36(4), 1245– 1257 (2020)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.436048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 26a019fe-a9c5-4bd9-97fc-db9969f6130f · outbound

This paper cites In: 2020 IEEE Region 10 Conference (TENCON), pp.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network In: 2020 IEEE Region 10 Conference (TENCON), pp

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.417195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fa5e162a-3f56-430f-8f42-b13957559f0f · outbound

This paper cites Computers in Industry 109, 121–133 (2019).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Computers in Industry 109, 121–133 (2019)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.400747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8eb753f5-0663-4925-be1f-aa0e49f8a4b6 · outbound

This paper cites Neurocomputing 139, 84–96 (2014).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Neurocomputing 139, 84–96 (2014)

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.383836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1b7bf068-5306-41cf-babe-24ba67ff8e93 · outbound

This paper cites In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network In: 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.365671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5e87bf97-e1e5-46d0-a5f7-9772b5ac1035 · outbound

This paper cites IEEE Transactions on Semiconductor Manufacturing 32(2), 163–170 (2019).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network IEEE Transactions on Semiconductor Manufacturing 32(2), 163–170 (2019)

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.347937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0acd0fc1-4c18-4e5b-a860-7d0b9e3146f4 · outbound

This paper cites Quality Engineering, 1–15 (2023).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Quality Engineering, 1–15 (2023)

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.330254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d76c6c2e-cee8-439f-b75b-54beec0faccb · outbound

This paper cites In: 2022 IEEE Delhi Section Conference (DELCON), pp.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network In: 2022 IEEE Delhi Section Conference (DELCON), pp

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.308481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e895add4-3dee-4126-adf0-430e57e8f1f5 · outbound

This paper cites Applied measurement in education 9(4), 355–379 (1996).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Applied measurement in education 9(4), 355–379 (1996)

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.286983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eb54417d-ceb4-44f3-8f11-4edf64ae8fc4 · outbound

This paper cites 620, 1st edn.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network 620, 1st edn

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.267637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ec98fe84-c7fe-463b-b208-7abfb580360a · outbound

This paper cites Journal of Educational and Behavioral Statistics 45(2), 227–248 (2020).

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Journal of Educational and Behavioral Statistics 45(2), 227–248 (2020)

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.247059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8fbaadef-e0d5-4b6d-8b06-7303f2413acf · outbound

This paper cites Programming with TensorFlow: solution for edge computing applications, 87–104 (2021) 26.

Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network Programming with TensorFlow: solution for edge computing applications, 87–104 (2021) 26

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T19:07:07.226827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 461f36c9-bc3a-4e56-9aef-4fbc4dd048e2 · inbound

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques cites this paper.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-16T00:45:02.599821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.