Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques | Paper Citation Record

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This paper cites WSTS Semiconductor Market Forecast Fall 2024 (2025).

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques WSTS Semiconductor Market Forecast Fall 2024 (2025)

Reference 1

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This paper cites The Role of Semiconductors in Emerging Technologies like AI and 5G (2025) https://www.einfochips.com/blog/the-role-of-semiconductors-in-emerging- technologies-like-ai-and-5g/.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques The Role of Semiconductors in Emerging Technologies like AI and 5G (2025) https://www.einfochips.com/blog/the-role-of-semiconductors-in-emerging- technologies-like-ai-and-5g/

Reference 2

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This paper cites an unresolved cited work.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Unresolved cited work

Reference 3

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This paper cites Integration of AI and Machine Learning in Semiconductor Manufacturing for Defect Detection and Yield Improvement.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Integration of AI and Machine Learning in Semiconductor Manufacturing for Defect Detection and Yield Improvement

Reference 4

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This paper cites and Balakrishnan R.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques and Balakrishnan R

Reference 5

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This paper cites , Shin M.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques , Shin M

Reference 6

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This paper cites & Lee, CO.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques & Lee, CO

Reference 7

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This paper cites , Sánchez-Reolid R.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques , Sánchez-Reolid R

Reference 8

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This paper cites Iterative Cluster Harvesting for Wafer Map Defect Patterns.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Iterative Cluster Harvesting for Wafer Map Defect Patterns

Reference 9

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This paper cites A novel DBSCAN-based defect pattern detection and classification framework for wafer bin map (2019).

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A novel DBSCAN-based defect pattern detection and classification framework for wafer bin map (2019)

Reference 10

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This paper cites Detection and clustering of mixed-type defect patterns in wafer bin maps.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Detection and clustering of mixed-type defect patterns in wafer bin maps

Reference 11

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This paper cites A self-adaptive DBSCAN-based method for wafer bin map defect pattern classification.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A self-adaptive DBSCAN-based method for wafer bin map defect pattern classification

Reference 12

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This paper cites Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Clustering high-dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering

Reference 13

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This paper cites Enabling DBSCAN for Very Large-Scale High-Dimensional Spaces.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Enabling DBSCAN for Very Large-Scale High-Dimensional Spaces

Reference 14

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This paper cites Anomaly detection and improvement of clusters using enhanced k- means algorithm.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Anomaly detection and improvement of clusters using enhanced k- means algorithm

Reference 15

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This paper cites An improved and heuristic-based iterative DBSCAN clustering algorithm.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques An improved and heuristic-based iterative DBSCAN clustering algorithm

Reference 16

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This paper cites A novel approach for wafer defect pattern classification based on topological data analysis.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A novel approach for wafer defect pattern classification based on topological data analysis

Reference 17

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This paper cites A novel quality clustering methodology on fab-wide wafer map images in semiconductor manufacturing.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A novel quality clustering methodology on fab-wide wafer map images in semiconductor manufacturing

Reference 18

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This paper cites Explainable machine learning approach to yield and quality improvements using deep topological data analytics.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Explainable machine learning approach to yield and quality improvements using deep topological data analytics

Reference 19

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This paper cites Self-supervised representation learning for wafer bin map defect pattern classification.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Self-supervised representation learning for wafer bin map defect pattern classification

Reference 20

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This paper cites When wafer failure pattern classification meets few- shot learning and self-supervised learning.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques When wafer failure pattern classification meets few- shot learning and self-supervised learning

Reference 21

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This paper cites A momentum contrastive learning framework for low-data wafer defect classification in semiconductor manufacturing.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A momentum contrastive learning framework for low-data wafer defect classification in semiconductor manufacturing

Reference 22

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Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Variational deep clustering of wafer map patterns

Reference 23

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This paper cites Dynamic clustering for wafer map patterns using self-supervised learning on convolutional autoencoders.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Dynamic clustering for wafer map patterns using self-supervised learning on convolutional autoencoders

Reference 24

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This paper cites Anomaly detection and segmentation for wafer defect patterns using deep convolutional encoder–decoder neural network architectures in semiconductor manufacturing.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Anomaly detection and segmentation for wafer defect patterns using deep convolutional encoder–decoder neural network architectures in semiconductor manufacturing

Reference 25

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This paper cites A CNN-based transfer learning method for defect classification in semiconductor manufacturing.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A CNN-based transfer learning method for defect classification in semiconductor manufacturing

Reference 26

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Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Anomaly detection in batch manufacturing processes using localized reconstruction errors from 1-d convolutional autoencoders

Reference 27

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Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Convolutional autoencoders for anomaly detection in semiconductor manufacturing

Reference 28

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Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Physics-prior Bayesian neural networks in semiconductor processing

Reference 29

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This paper cites A patch-interactive enhancement network for semiconductor wafer map mixed defect recognition with a two-stage training strategy.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A patch-interactive enhancement network for semiconductor wafer map mixed defect recognition with a two-stage training strategy

Reference 30

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Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Transfer Learning-Based Defect Detection System on Wafer Surfaces

Reference 31

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This paper cites A CNN-based transfer learning method for defect classification in semiconductor manufacturing.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A CNN-based transfer learning method for defect classification in semiconductor manufacturing

Reference 32

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This paper cites Few-shot classification of wafer bin maps using transfer learning and ensemble learning.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Few-shot classification of wafer bin maps using transfer learning and ensemble learning

Reference 33

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This paper cites An EfficientNet-Based Transfer Learning System for Defect Classification in Manufacturing.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques An EfficientNet-Based Transfer Learning System for Defect Classification in Manufacturing

Reference 34

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Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Unresolved cited work

Reference 35

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This paper cites AI Deep-Learning Approach for Manufacturing Optimization During Chiplets and Heterogeneous Package Inspection,.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques AI Deep-Learning Approach for Manufacturing Optimization During Chiplets and Heterogeneous Package Inspection,

Reference 36

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This paper cites Advanced Techniques in Semiconductor Defect Detection and Classification: Overview of Current Technologies and Future Trends in AI/ML Integration,.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Advanced Techniques in Semiconductor Defect Detection and Classification: Overview of Current Technologies and Future Trends in AI/ML Integration,

Reference 37

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This paper cites Integration of AI and Machine Learning in Semiconductor Manufacturing for Defect Detection and Yield Improvement.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Integration of AI and Machine Learning in Semiconductor Manufacturing for Defect Detection and Yield Improvement

Reference 38

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This paper cites A Machine Learning-Based Method for Assisted Analysis and Decision Making of Wafer Yield.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A Machine Learning-Based Method for Assisted Analysis and Decision Making of Wafer Yield

Reference 39

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This paper cites A momentum contrastive learning framework for low-data wafer defect classification in semiconductor manufacturing.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A momentum contrastive learning framework for low-data wafer defect classification in semiconductor manufacturing

Reference 40

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This paper cites Self-supervised representation learning for wafer bin map defect pattern classification.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Self-supervised representation learning for wafer bin map defect pattern classification

Reference 41

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Observation d538e6ce-e53d-4928-81f3-efe081e898f4 · outbound

This paper cites Application of Self-Supervised Contrastive Learning for Mixed- Type Wafer Map Defect Recognition and Classification.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Application of Self-Supervised Contrastive Learning for Mixed- Type Wafer Map Defect Recognition and Classification

Reference 42

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Observation e6f74ae7-12b3-49a3-9573-9a9ed9704ef6 · outbound

This paper cites Unsupervised representation learning for large-scale wafer maps in micro-electronic manufacturing.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Unsupervised representation learning for large-scale wafer maps in micro-electronic manufacturing

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.633875Z

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Observation 7145ef99-85a9-45e9-8bd0-47a6ed112a30 · outbound

This paper cites Dynamic clustering for wafer map patterns using self-supervised learning on convolutional autoencoders.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Dynamic clustering for wafer map patterns using self-supervised learning on convolutional autoencoders

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.619832Z

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

This paper cites Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network.

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

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

Observation 88e72e66-2add-4431-9d77-4c9a784c4e2c · outbound

This paper cites A systematic review of deep learning for silicon wafer defect recognition.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A systematic review of deep learning for silicon wafer defect recognition

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.605150Z

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

Observation a5abb981-4fc5-425b-850e-bd6a01b404a2 · outbound

This paper cites AI in semiconductor industry.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques AI in semiconductor industry

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.590630Z

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

Observation f910e70f-3ab6-4e8a-b77d-24e457fb926d · outbound

This paper cites Wafer bin map recognition with autoencoder-based data augmentation in semiconductor assembly process.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Wafer bin map recognition with autoencoder-based data augmentation in semiconductor assembly process

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.575970Z

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 d69e0ac8-3a94-4b10-bbcf-c10badc0e21d · outbound

This paper cites Multiple granularities generative adversarial network for recognition of wafer map defects.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Multiple granularities generative adversarial network for recognition of wafer map defects

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.560859Z

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 87a70614-937f-4147-be9a-2a98c59d3a01 · outbound

This paper cites An analog wafer map clustering model with deep-learning based data augmentation and feature extraction.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques An analog wafer map clustering model with deep-learning based data augmentation and feature extraction

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.546706Z

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 fd4877cf-02a4-4c49-b521-43f3dc3ab3ea · outbound

This paper cites Improving automated visual fault inspection for semiconductor manufacturing using a hybrid multistage system of deep neural networks.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Improving automated visual fault inspection for semiconductor manufacturing using a hybrid multistage system of deep neural networks

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.518675Z

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 6a5f3d84-970c-4934-84d3-fb95ed3682ba · outbound

This paper cites Hybrid Deep Learning Pipeline for Advanced Electrical Wafer Defect Maps Assessment.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Hybrid Deep Learning Pipeline for Advanced Electrical Wafer Defect Maps Assessment

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.504621Z

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 0019c2f9-6ded-4750-b7bf-05c5c10800c0 · outbound

This paper cites Explainable deep learning system for advanced silicon and silicon carbide electrical wafer defect map assessment.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Explainable deep learning system for advanced silicon and silicon carbide electrical wafer defect map assessment

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.490528Z

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 12015b22-b14a-49be-90f0-83aed137775f · outbound

This paper cites Automated Anomaly Detection Through Assembly and Packaging Process.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Automated Anomaly Detection Through Assembly and Packaging Process

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.476253Z

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 d83e9ab4-0ab7-49f9-a2d6-4f4608eacf78 · outbound

This paper cites Defective wafer detection using a denoising autoencoder for semiconductor manufacturing processes.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Defective wafer detection using a denoising autoencoder for semiconductor manufacturing processes

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.462359Z

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 0c624cc7-fe43-4210-aef9-b0037acb3e0a · outbound

This paper cites A self-training-based system for die defect classification.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A self-training-based system for die defect classification

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.447459Z

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 f4373ff4-d6fc-48d5-b289-2877fe0387a4 · outbound

This paper cites AI-Based Localization and Classification of Visual Anomalies on Semiconductor Devices.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques AI-Based Localization and Classification of Visual Anomalies on Semiconductor Devices

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.432975Z

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 a4218be8-d030-4e48-900b-359975fe3004 · outbound

This paper cites Deep convolutional generative adversarial networks-based data augmentation method for classifying class-imbalanced defect patterns in wafer bin map.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Deep convolutional generative adversarial networks-based data augmentation method for classifying class-imbalanced defect patterns in wafer bin map

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.418567Z

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 117aab6a-a622-4788-b90a-38ac280f74d5 · outbound

This paper cites Building manufacturing deep learning models with minimal and imbalanced training data using domain adaptation and data augmentation.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Building manufacturing deep learning models with minimal and imbalanced training data using domain adaptation and data augmentation

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.403336Z

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 c17ce862-0bd6-4a09-9153-3f4b47be0b1c · outbound

This paper cites Wafer defect pattern labeling and recognition using semi-supervised learning.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Wafer defect pattern labeling and recognition using semi-supervised learning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.388634Z

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 e9e80926-f191-499d-b3c4-16acb9e0ce77 · outbound

This paper cites A Masked Autoencoder-Based Approach for Defect Classification in Semiconductor Manufacturing.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques A Masked Autoencoder-Based Approach for Defect Classification in Semiconductor Manufacturing

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.374041Z

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 0783ee1b-733d-4586-b3d7-f3988b556dae · outbound

This paper cites Enhancing defect diagnosis and localization in wafer map testing through weakly supervised learning.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Enhancing defect diagnosis and localization in wafer map testing through weakly supervised learning

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.358607Z

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 98559e2e-2c57-49be-b877-62e8ae4c41a2 · outbound

This paper cites Anomalous Wafer Map Detection and Localization using Unsupervised Learning.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Anomalous Wafer Map Detection and Localization using Unsupervised Learning

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.343839Z

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 59cf79f8-0ca7-48ca-9f99-82a7786d465c · outbound

This paper cites Unsupervised Defect Detection Based on Fast Retrieval of Deep Feature.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Unsupervised Defect Detection Based on Fast Retrieval of Deep Feature

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.329659Z

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 308ede71-180a-45d7-85d6-73bcedefa20c · outbound

This paper cites Unsupervised Wafer Defect Classification Model Based On Joint Reconstruction And Clustering.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Unsupervised Wafer Defect Classification Model Based On Joint Reconstruction And Clustering

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.315367Z

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 e3140997-e6a9-4533-b7da-7365c370ca4e · outbound

This paper cites Adaptive modelling for anomaly detection and defect diagnosis in semiconductor smart manufacturing: A domain-specific automl.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Adaptive modelling for anomaly detection and defect diagnosis in semiconductor smart manufacturing: A domain-specific automl

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.300963Z

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 65ac1a01-d7ef-4a97-a902-04d61ba7e866 · outbound

This paper cites Wafer map defect patterns semi-supervised classification using latent vector representation.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Wafer map defect patterns semi-supervised classification using latent vector representation

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.286727Z

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 de928274-4a72-440f-a30b-dddc442b90be · outbound

This paper cites Joint feature and label adversarial network for wafer map defect recognition.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Joint feature and label adversarial network for wafer map defect recognition

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.272332Z

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 4a9a5ba0-ad23-49cf-9469-ea1ee7bbed81 · outbound

This paper cites Unsupervised pre-training of imbalanced data for identification of wafer map defect patterns.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Unsupervised pre-training of imbalanced data for identification of wafer map defect patterns

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.533073Z

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 2467e929-1c65-4ac3-84b3-78e250e50588 · outbound

This paper cites Identification of key features using topological data analysis for accurate prediction of manufacturing system outputs.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Identification of key features using topological data analysis for accurate prediction of manufacturing system outputs

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.258382Z

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 31ccbb11-28a7-451e-a622-b301af008903 · outbound

This paper cites Topological Data Analysis in smart manufacturing: State of the art and future directions.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Topological Data Analysis in smart manufacturing: State of the art and future directions

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.243316Z

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 fdf3d135-c993-4103-b6b3-a4b6fdb649a3 · outbound

This paper cites Recent Applications Using Explainable Artificial Intelligence for Data Analytics.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Recent Applications Using Explainable Artificial Intelligence for Data Analytics

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.228802Z

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 cecd5ae6-b335-462a-8a79-dbffc14abe35 · outbound

This paper cites The Applications of Simulation and Artificial Intelligence in Advanced Packaging.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques The Applications of Simulation and Artificial Intelligence in Advanced Packaging

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.214422Z

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 1798b1ab-9512-436a-8b19-6175caa20301 · outbound

This paper cites Wafer map failure pattern recognition and similarity ranking for large-scale data sets.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Wafer map failure pattern recognition and similarity ranking for large-scale data sets

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.199608Z

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 a9be0ab1-3077-47c7-9e20-d0f0fe507158 · outbound

This paper cites Deformable convolutional networks for efficient mixed-type wafer defect pattern recognition.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Deformable convolutional networks for efficient mixed-type wafer defect pattern recognition

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.184285Z

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 604a318d-9ffe-43f4-944c-183ffde19fd9 · outbound

This paper cites an unresolved cited work.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Unresolved cited work

Reference 77

Resolution: unresolved; raw_fallback, observed 2026-08-16T00:45:03.169173Z

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 c4411fc2-ad18-45b0-b4dd-b096c0a1b984 · outbound

This paper cites Topological methods for data modelling.

Advanced Clustering Framework for Semiconductor Image Analytics Integrating Deep TDA with Self-Supervised and Transfer Learning Techniques Topological methods for data modelling

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:45:03.154384Z

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.

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Reference resolution

Outbound references

Pith citing papers