9 citations · 14 across the 4 of their papers we have counts for
6 papers
Single-pass Possibilistic Clustering with Damped Window Footprints
Jeffrey Dale, James Keller, Aquila Galusha
Streaming clustering is a domain that has become extremely relevant in the age of big data, such as in network traffic analysis or in processing continuously-running sensor data. F…
Histogram Layers for Synthetic Aperture Sonar Imagery
Joshua Peeples, Alina Zare, Jeffrey Dale +1
Synthetic aperture sonar (SAS) imagery is crucial for several applications, including target recognition and environmental segmentation. Deep learning models have led to much succe…
The Weakly-Labeled Rand Index
Dylan Stewart, Anna Hampton, Alina Zare +2
Synthetic Aperture Sonar (SAS) surveys produce imagery with large regions of transition between seabed types. Due to these regions, it is difficult to label and segment the imagery…
Explainable Systematic Analysis for Synthetic Aperture Sonar Imagery
Sarah Walker, Joshua Peeples, Jeff Dale +2
In this work, we present an in-depth and systematic analysis using tools such as local interpretable model-agnostic explanations (LIME) (arXiv:1602.04938) and divergence measures t…
Divergence Regulated Encoder Network for Joint Dimensionality Reduction and Classification
Joshua Peeples, Sarah Walker, Connor McCurley +3
Feature representation is an important aspect of remote-sensing based image classification. While deep convolutional neural networks are able to effectively amalgamate information,…
Comparison of Possibilistic Fuzzy Local Information C-Means and Possibilistic K-Nearest Neighbors for Synthetic Aperture Sonar Image Segmentation
Joshua Peeples, Matthew Cook, Daniel Suen +2
Synthetic aperture sonar (SAS) imagery can generate high resolution images of the seafloor. Thus, segmentation algorithms can be used to partition the images into different seafloo…