37 citations · 41 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 37 cited
Understanding and Combating Robust Overfitting via Input Loss Landscape Analysis and Regularization
Lin Li, Michael Spratling
Adversarial training is widely used to improve the robustness of deep neural networks to adversarial attack. However, adversarial training is prone to overfitting, and the cause is…
cs.CV2022
CobNet: Cross Attention on Object and Background for Few-Shot Segmentation
Haoyan Guan, Michael Spratling
Few-shot segmentation aims to segment images containing objects from previously unseen classes using only a few annotated samples. Most current methods focus on using object inform…
cs.CV2016★ 4 cited
A three-dimensional approach to Visual Speech Recognition using Discrete Cosine Transforms
Toni Heidenreich, Michael W. Spratling
Visual speech recognition aims to identify the sequence of phonemes from continuous speech. Unlike the traditional approach of using 2D image feature extraction methods to derive f…