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Found 8 papers, 1 papers with code
Making the Invisible Visible: Toward High-Quality Terahertz Tomographic Imaging via Physics-Guided Restoration
Terahertz (THz) tomographic imaging has recently attracted significant attention thanks to its non-invasive, non-destructive, non-ionizing, material-classification, and ultra-fast nature for object exploration and inspection.
Kinship Representation Learning with Face Componential Relation
Kinship recognition aims to determine whether the subjects in two facial images are kin or non-kin, which is an emerging and challenging problem.
Physics-guided Terahertz Computational Imaging
Visualizing information inside objects is an ever-lasting need to bridge the world from physics, chemistry, biology to computation.
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.
SiGAN: Siamese Generative Adversarial Network for Identity-Preserving Face Hallucination
Despite generative adversarial networks (GANs) can hallucinate photo-realistic high-resolution (HR) faces from low-resolution (LR) faces, they cannot guarantee preserving the identities of hallucinated HR faces, making the HR faces poorly recognizable.
Graph Fourier Transform with Negative Edges for Depth Image Coding
Recent advent in graph signal processing (GSP) has led to the development of new graph-based transforms and wavelets for image / video coding, where the underlying graph describes inter-pixel correlations.
Robust Semi-Supervised Graph Classifier Learning with Negative Edge Weights
In response, we derive an optimal perturbation matrix $\boldsymbol{\Delta}$ - based on a fast lower-bound computation of the minimum eigenvalue of $\mathbf{L}$ via a novel application of the Haynsworth inertia additivity formula---so that $\mathbf{L} + \boldsymbol{\Delta}$ is positive semi-definite, resulting in a stable signal prior.
