Life Sciences Commons^™

Semi-Supervised Adversarial Domain Adaptation For Seagrass Detection Using Multispectral Images In Coastal Areas, Kazi Aminul Islam, Victoria Hill, Blake Schaeffer, Richard Zimmerman, Jiang Li

Electrical & Computer Engineering Faculty Publications

Seagrass form the basis for critically important marine ecosystems. Previously, we implemented a deep convolutional neural network (CNN) model to detect seagrass in multispectral satellite images of three coastal habitats in northern Florida. However, a deep CNN model trained at one location usually does not generalize to other locations due to data distribution shifts. In this paper, we developed a semi-supervised domain adaptation method to generalize a trained deep CNN model to other locations for seagrass detection. First, we utilized a generative adversarial network loss to align marginal data distribution between source domain and target domain using unlabeled data from …