2 citations · 2 across the 8 of their papers we have counts for
5 papers · 1 filter
Visualizing the embedding space to explain the effect of knowledge distillation
Hyun Seung Lee, Christian Wallraven
Recent research has found that knowledge distillation can be effective in reducing the size of a network and in increasing generalization. A pre-trained, large teacher network, for…
Comparing Facial Expression Recognition in Humans and Machines: Using CAM, GradCAM, and Extremal Perturbation
Serin Park, Christian Wallraven
Facial expression recognition (FER) is a topic attracting significant research in both psychology and machine learning with a wide range of applications. Despite a wealth of resear…
Label quality in AffectNet: results of crowd-based re-annotation
Doo Yon Kim, Christian Wallraven
AffectNet is one of the most popular resources for facial expression recognition (FER) on relatively unconstrained in-the-wild images. Given that images were annotated by only one…
Predicting decision-making in the future: Human versus Machine
Hoe Sung Ryu, Uijong Ju, Christian Wallraven
Deep neural networks (DNNs) have become remarkably successful in data prediction, and have even been used to predict future actions based on limited input. This raises the question…
Paperswithtopic: Topic Identification from Paper Title Only
Daehyun Cho, Christian Wallraven
The deep learning field is growing rapidly as witnessed by the exponential growth of papers submitted to journals, conferences, and pre-print servers. To cope with the sheer number…