Our framework incorporates an encoder to learn good representation for wafer maps in an unsupervised manner, and a supervised head to recognize wafer map ...

Dec 26, 2023 · Recognizing Wafer Map Patterns Using Semi-Supervised Contrastive Learning with Optimized Latent Representation Learning and Data Augmentation.

Hu et al. (2021) proposed a contrastive learning framework for singletype defect patterns, followed by supervised finetuning of a classifier. Despite ...

Recognizing Wafer Map Patterns Using Semi-Supervised Contrastive Learning with Optimized Latent Representation Learning and Data Augmentation. Z Wang, H Hu ...

Recognizing Wafer Map Patterns Using Semi-Supervised Contrastive Learning with Optimized Latent Representation Learning and Data Augmentation. Z Wang, H Hu ...

This paper proposes a novel semi-supervised contrastive learning framework for wafer map pattern feature extraction and classification. Our framework uses ...

Apr 25, 2024 · Recognizing Wafer Map Patterns Using Semi-Supervised Contrastive Learning with Optimized Latent Representation Learning and Data Augmentation.

It is demonstrated that rotation-based data augmentation can effectively improve wafer map pattern classification when training data are scarce and provide ...

Missing: Contrastive | Show results with:Contrastive

Recognizing wafer map patterns using semi-supervised contrastive learning with optimized latent representation learning and data augmentation. In 2023 IEEE.