18 citations · 41 across the 9 of their papers we have counts for
3 papers · 1 filter
OrigamiSet1.0: Two New Datasets for Origami Classification and Difficulty Estimation
Daniel Ma, Gerald Friedland, Mario Michael Krell
Origami is becoming more and more relevant to research. However, there is no public dataset yet available and there hasn't been any research on this topic in machine learning. We c…
Efficient Saliency Maps for Explainable AI
T. Nathan Mundhenk, Barry Y. Chen, Gerald Friedland
We describe an explainable AI saliency map method for use with deep convolutional neural networks (CNN) that is much more efficient than popular fine-resolution gradient methods. I…
The Helmholtz Method: Using Perceptual Compression to Reduce Machine Learning Complexity
Gerald Friedland, Jingkang Wang, Ruoxi Jia +1
This paper proposes a fundamental answer to a frequently asked question in multimedia computing and machine learning: Do artifacts from perceptual compression contribute to error i…