Acoustic classification in multifrequency echosounder data using deep convolutional neural networks

Acoustic target classification is the process of assigning observed acoustic backscattering intensity to an acoustic category. A deep learning strategy for acoustic target classification using a convolutional network is developed, consisting of an encoder and a decoder, which allow the network to use pixel information and more abstract features. The network can learn features directly from data, and the learned feature space may include both...