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Found 5 papers, 0 papers with code
SDeMorph: Towards Better Facial De-morphing from Single Morph
In this work, we propose SDeMorph (Stably Diffused De-morpher), a novel de-morphing method that is reference-free and recovers the identities of bona fides.
Generating Adversarial Attacks in the Latent Space
Adversarial attacks in the input (pixel) space typically incorporate noise margins such as $L_1$ or $L_{\infty}$-norm to produce imperceptibly perturbed data that confound deep learning networks.
Mixed-Type Wafer Classification For Low Memory Devices Using Knowledge Distillation
We empirically show that this type of training compresses the model without sacrificing accuracy despite being up to 10 times smaller than the teacher model.
Efficient Mixed-Type Wafer Defect Pattern Recognition Using Compact Deformable Convolutional Transformers
Mixed-type DPR is much more complicated compared to single-type DPR due to varied spatial features, the uncertainty of defects, and the number of defects present.
An Embarrassingly Simple Approach for Wafer Feature Extraction and Defect Pattern Recognition
All these issues make these models not fit for on-line prediction in the manufacturing foundry.
