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Iterative, Deep Synthetic Aperture Sonar Image Segmentation
IDUS is an unsupervised learning framework that can be divided into four main steps: 1) A deep network estimates class assignments.
Iterative, Deep, and Unsupervised Synthetic Aperture Sonar Image Segmentation
Our results show that the performance of our proposed method is considerably better than current state-of-the-art methods in SAS image segmentation.
Multi-Class Micro-CT Image Segmentation Using Sparse Regularized Deep Networks
It is common in anthropology and paleontology to address questions about extant and extinct species through the quantification of osteological features observable in micro-computed tomographic (micro-CT) scans.
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