28 citations · 53 across the 5 of their papers we have counts for
6 papers
Advances in Self-Supervised Learning for Synthetic Aperture Sonar Data Processing, Classification, and Pattern Recognition
Brandon Sheffield, Frank E. Bobe, Bradley Marchand +1
Synthetic Aperture Sonar (SAS) imaging has become a crucial technology for underwater exploration because of its unique ability to maintain resolution at increasing ranges, a chara…
Target Detection and Segmentation in Circular-Scan Synthetic-Aperture-Sonar Images using Semi-Supervised Convolutional Encoder-Decoders
Isaac J. Sledge, Matthew S. Emigh, Jonathan L. King +3
We propose a framework for saliency-based, multi-target detection and segmentation of circular-scan, synthetic-aperture-sonar (CSAS) imagery. Our framework relies on a multi-branch…
Algorithmic Design and Implementation of Unobtrusive Multistatic Serial LiDAR Image
Chi Ding, Zheng Cao, Matthew S. Emigh +6
To fully understand interactions between marine hydrokinetic (MHK) equipment and marine animals, a fast and effective monitoring system is required to capture relevant information…
Guided Policy Exploration for Markov Decision Processes using an Uncertainty-Based Value-of-Information Criterion
Isaac J. Sledge, Matthew S. Emigh, Jose C. Principe
Reinforcement learning in environments with many action-state pairs is challenging. At issue is the number of episodes needed to thoroughly search the policy space. Most convention…
Exploiting Spatio-Temporal Structure with Recurrent Winner-Take-All Networks
Eder Santana, Matthew Emigh, Pablo Zegers +1
We propose a convolutional recurrent neural network, with Winner-Take-All dropout for high dimensional unsupervised feature learning in multi-dimensional time series. We apply the…
Information Theoretic-Learning Auto-Encoder
Eder Santana, Matthew Emigh, Jose C Principe
We propose Information Theoretic-Learning (ITL) divergence measures for variational regularization of neural networks. We also explore ITL-regularized autoencoders as an alternativ…