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A Deep Learning Approach to Target Recognition in Side-scan Sonar Imagery
Başlık:
A Deep Learning Approach to Target Recognition in Side-scan Sonar Imagery
Yazar:
Einsidler, Dylan, author.
ISBN:
9780438013056
Yazar Ek Girişi:
Fiziksel Tanımlama:
1 electronic resource (109 pages)
Genel Not:
Source: Masters Abstracts International, Volume: 57-06M(E).
Advisors: Manhar Dhanak Committee members: Pierre-Philippe Beaujean; Oscar Curet; Manhar Dhanak.
Özet:
Automatic target recognition capabilities in autonomous underwater vehicles has been a daunting task, largely due to the noisy nature of sonar imagery and due to the lack of publicly available sonar data. Machine learning techniques have made great strides in tackling this feat, although not much research has been done regarding deep learning techniques for side-scan sonar imagery. Here, a state-of-the-art deep learning object detection method is adapted for side-scan sonar imagery, with results supporting a simple yet robust method to detect objects/anomalies along the seabed. A systematic procedure was employed in transfer learning a pre-trained convolutional neural network in order to learn the pixel-intensity based features of seafloor anomalies in sonar images. Using this process, newly trained convolutional neural network models were produced using relatively small training datasets and tested to show reasonably accurate anomaly detection and classification with little to no false alarms.
Notlar:
School code: 0119
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Yer Numarası | Demirbaş Numarası | Shelf Location | Lokasyon / Statüsü / İade Tarihi |
---|---|---|---|
XX(691638.1) | 691638-1001 | Proquest E-Tez Koleksiyonu | Arıyor... |
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