82 citations · 119 across the 3 of their papers we have counts for
7 papers
Fuzzy Integral = Contextual Linear Order Statistic
Derek Anderson, Matthew Deardorff, Timothy Havens +5
The fuzzy integral is a powerful parametric nonlin-ear function with utility in a wide range of applications, from information fusion to classification, regression, decision making…
Introducing Fuzzy Layers for Deep Learning
Stanton R. Price, Steven R. Price, Derek T. Anderson
Many state-of-the-art technologies developed in recent years have been influenced by machine learning to some extent. Most popular at the time of this writing are artificial intell…
Extending the Morphological Hit-or-Miss Transform to Deep Neural Networks
Muhammad Aminul Islam, Bryce Murray, Andrew Buck +4
While most deep learning architectures are built on convolution, alternative foundations like morphology are being explored for purposes like interpretability and its connection to…
Fusion of heterogeneous bands and kernels in hyperspectral image processing
Muhammad Aminul Islam, Derek T. Anderson, John E. Ball +1
Hyperspectral imaging is a powerful technology that is plagued by large dimensionality. Herein, we explore a way to combat that hindrance via non-contiguous and contiguous (simpler…
Enabling Explainable Fusion in Deep Learning with Fuzzy Integral Neural Networks
Muhammad Aminul Islam, Derek T. Anderson, Anthony J. Pinar +3
Information fusion is an essential part of numerous engineering systems and biological functions, e.g., human cognition. Fusion occurs at many levels, ranging from the low-level co…
State-of-the-art and gaps for deep learning on limited training data in remote sensing
John E. Ball, Derek T. Anderson, Pan Wei
Deep learning usually requires big data, with respect to both volume and variety. However, most remote sensing applications only have limited training data, of which a small subset…