5 citations · 8 across the 9 of their papers we have counts for
9 papers
Unveiling the Power of Sparse Neural Networks for Feature Selection
Zahra Atashgahi, Tennison Liu, Mykola Pechenizkiy +3
Sparse Neural Networks (SNNs) have emerged as powerful tools for efficient feature selection. Leveraging the dynamic sparse training (DST) algorithms within SNNs has demonstrated p…
E2F-Net: Eyes-to-Face Inpainting via StyleGAN Latent Space
Ahmad Hassanpour, Fatemeh Jamalbafrani, Bian Yang +3
Face inpainting, the technique of restoring missing or damaged regions in facial images, is pivotal for applications like face recognition in occluded scenarios and image analysis…
Efficient Expression Neutrality Estimation with Application to Face Recognition Utility Prediction
Marcel Grimmer, Raymond N. J. Veldhuis, Christoph Busch
The recognition performance of biometric systems strongly depends on the quality of the compared biometric samples. Motivated by the goal of establishing a common understanding of…
What do neural networks learn in image classification? A frequency shortcut perspective
Shunxin Wang, Raymond Veldhuis, Christoph Brune +1
Frequency analysis is useful for understanding the mechanisms of representation learning in neural networks (NNs). Most research in this area focuses on the learning dynamics of NN…
NeutrEx: A 3D Quality Component Measure on Facial Expression Neutrality
Marcel Grimmer, Christian Rathgeb, Raymond Veldhuis +1
Accurate face recognition systems are increasingly important in sensitive applications like border control or migration management. Therefore, it becomes crucial to quantify the qu…
DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut Learning
Shunxin Wang, Christoph Brune, Raymond Veldhuis +1
Neural networks are prone to learn easy solutions from superficial statistics in the data, namely shortcut learning, which impairs generalization and robustness of models. We propo…