Seabed type and source parameters predictions using ship spectrograms in convolutional neural networks von Van Komen, David F, Neilsen, Tracianne B, Mortenson, Daniel B, Acree, Mason C, Knobles, David P, Badiey, Mohsen, Hodgkiss, William S

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Applications of semi-supervised learning methods in underwater acoustics von Acree, Mason C., Neilsen, Tracianne B., Knobles, David P.

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Seabed type and source parameters predictions using ship spectrograms in convolutional neural networksa von Van Komen, David F., Neilsen, Tracianne B., Mortenson, Daniel B., Acree, Mason C., Knobles, David P., Badiey, Mohsen, Hodgkiss, William S.

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Semi-supervised deep learning of source location and seabed class from unlabeled merchant ships in the shallow ocean von Acree, Mason C., Neilsen, Tracianne B., Knobles, David P., Hodgkiss, William

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Sound classification during Seabed Classification Experiment 2017 von Earnhardt, Allison N., Neilsen, Tracianne B., Acree, Mason C., Hodgkiss, William, Knobles, David P.

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A deep learning approach to source localization and seabed classification using pressure time-series from a vertical array von Acree, Mason C., Van Komen, David F., Neilsen, Tracianne B., Knobles, David P.

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Effect of environmental uncertainty on source localization from mid-frequency tonals using convolutional neural networks von Neilsen, Tracianne B., Escobar, Christian, Acree, Mason C., Hodgkiss, William, Van Komen, David F., Knobles, David P., Badiey, Mohsen, Castro-Correa, Jhon A.

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Sound Signal Classification in the New England Mud Patch von Earnhardt, Allison N., Neilsen, Tracianne B., Acree, Mason C., Hodgkiss, William S., Knobles, D. P.

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The reward-based eating drive scale: a self-report index of reward-based eating von Epel, Elissa S, Tomiyama, A Janet, Mason, Ashley E, Laraia, Barbara A, Hartman, William, Ready, Karen, Acree, Michael, Adam, Tanja C, St Jeor, Sachiko, Kessler, David

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