Techniques for classifying maritime domain targets-of-interest within images are explored in this book. Geometric and photometric features within each image are extracted from processed images and are used to train a neural network. The trained neural network is tested with features of a known object. In the binary classification case, the neural network is used to determine whether a ship is present or not present in the image. In the multi-class and multi-level classification cases, the neural network is used to determine if the object belongs to one of four classes specified: warship, cargo ship, small boat, or other. The Hough transformation is used to identify and characterize linear patterns exhibited by objects in images. As an alternative to geometric and photometric features to classify targets-of-interest, these linear patterns are used to train a neural network. The performance of the neural network is then tested for binary, multi-class, and multi-level classification schemes. The development of neural-network-based techniques for automated target-of-interest classification is a significant result of this book.
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Paperback. Etat : new. Paperback. Techniques for classifying maritime domain targets-of-interest within images are explored in this book. Geometric and photometric features within each image are extracted from processed images and are used to train a neural network. The trained neural network is tested with features of a known object. In the binary classification case, the neural network is used to determine whether a ship is present or not present in the image. In the multi-class and multi-level classification cases, the neural network is used to determine if the object belongs to one of four classes specified: warship, cargo ship, small boat, or other. The Hough transformation is used to identify and characterize linear patterns exhibited by objects in images. As an alternative to geometric and photometric features to classify targets-of-interest, these linear patterns are used to train a neural network. The performance of the neural network is then tested for binary, multi-class, and multi-level classification schemes. The development of neural-network-based techniques for automated target-of-interest classification is a significant result of this book. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781522738244
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