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Found 6 papers, 1 papers with code
LithoHoD: A Litho Simulator-Powered Framework for IC Layout Hotspot Detection
However, by taking an object detection network as the backbone, recent learning-based hotspot detectors learn to recognize only the problematic layout patterns in the training data.
Keeping Deep Lithography Simulators Updated: Global-Local Shape-Based Novelty Detection and Active Learning
To address the problem, we propose a deep learning-based layout novelty detection scheme to identify novel (unseen) layout patterns, which cannot be well predicted by a pre-trained pre-simulation model.
Ensemble Learning with Manifold-Based Data Splitting for Noisy Label Correction
Here we focus on the problem that noisy labels are primarily mislabeled samples, which tend to be concentrated near decision boundaries, rather than uniformly distributed, and whose features should be equivocal.
Forgery Blind Inspection for Detecting Manipulations of Gel Electrophoresis Images
Recently, falsified images have been found in papers involved in research misconducts.
DotFAN: A Domain-transferred Face Augmentation Network for Pose and Illumination Invariant Face Recognition
With their aid, DotFAN can learn a disentangled face representation and effectively generate face images of various facial attributes while preserving the identity of augmented faces.
From IC Layout to Die Photo: A CNN-Based Data-Driven Approach
By learning the shape correspondences between pairs of layout design patterns and their scanning electron microscope (SEM) images of the product wafer thereof, given an IC layout pattern, LithoNet can mimic the fabrication process to predict its fabricated circuit shape.
