Seafloor classification using echo-waveforms: a method employing hybrid neural network architecture

This letter presents seafloor classification study results of a hybrid artificial neural network architecture known as learning vector quantization. Single beam echo-sounding backscatter waveform data from three different seafloors of the western continental shelf of India are utilized. In this letter, an analysis is presented to establish the hybrid network as an efficient alternative for real-time seafloor classification of the acoustic backscatter data.