# IEEE Transactions on Semiconductor Manufacturing

**Type:** Journals  
**Canonical URL:** https://scholariq.org/journals/ieee-transactions-on-semiconductor-manufacturing/

## Facts

| Field | Value |
| --- | --- |
| Open Access | false |
| ISSN-L | 0894-6507 |
| ISSNs | 0894-6507,1558-2345 |
| OpenAlex ID | https://openalex.org/S14676311 |
| Publisher | IEEE Computer Society |

## Journal papers

- [A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes](https://scholariq.org/papers/a-convolutional-neural-network-for-fault-classification-and-diagnosis-in/)
- [Convolutional Neural Network for Wafer Surface Defect Classification and the Detection of Unknown Defect Class](https://scholariq.org/papers/convolutional-neural-network-for-wafer-surface-defect-classification-and-the/)
- [Rapid characterization and modeling of pattern-dependent variation in chemical-mechanical polishing](https://scholariq.org/papers/rapid-characterization-and-modeling-of-pattern-dependent-variation-in-chemical/)
- [A Deep Learning Model for Robust Wafer Fault Monitoring With Sensor Measurement Noise](https://scholariq.org/papers/a-deep-learning-model-for-robust-wafer-fault-monitoring-with-sensor-measurement/)
- [Transfer-Learning-Based Online Mura Defect Classification](https://scholariq.org/papers/transfer-learning-based-online-mura-defect-classification/)
- [Performance of Machine Learning Algorithms for Class-Imbalanced Process Fault Detection Problems](https://scholariq.org/papers/performance-of-machine-learning-algorithms-for-class-imbalanced-process-fault/)
- [An Incremental Clustering-Based Fault Detection Algorithm for Class-Imbalanced Process Data](https://scholariq.org/papers/an-incremental-clustering-based-fault-detection-algorithm-for-class-imbalanced/)
- [Tool Condition Diagnosis With a Recipe-Independent Hierarchical Monitoring Scheme](https://scholariq.org/papers/tool-condition-diagnosis-with-a-recipe-independent-hierarchical-monitoring/)
- [Generative AI-Driven Data Augmentation for Robust Virtual Metrology: GANs, VAEs, and Diffusion Models](https://scholariq.org/papers/generative-ai-driven-data-augmentation-for-robust-virtual-metrology-gans-vaes/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.