13 citations · 22 across the 3 of their papers we have counts for
3 papers
cs.CV2021★ 13 cited
Possibilistic Fuzzy Local Information C-Means with Automated Feature Selection for Seafloor Segmentation
Joshua Peeples, Daniel Suen, Alina Zare +1
The Possibilistic Fuzzy Local Information C-Means (PFLICM) method is presented as a technique to segment side-look synthetic aperture sonar (SAS) imagery into distinct regions of t…
eess.IV2019★ 9 cited
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…
cs.CV2017
Possibilistic Fuzzy Local Information C-Means for Sonar Image Segmentation
Alina Zare, Nicholas Young, Daniel Suen +3
Side-look synthetic aperture sonar (SAS) can produce very high quality images of the sea-floor. When viewing this imagery, a human observer can often easily identify various sea-fl…