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In this study, we explore the possibility of recognizing hand gestures using ultrasonic depth imaging. The ultrasonic device consists of a single piezoelectric transducer and an 8 -element microphone array. Using carefully designed transmit pulse, and a combination of beamforming, matched filtering, and cross-correlation methods, we construct ultrasound images with depth and intensity pixels. Thereafter, we use a combined Convolutional (CNN) and Long Short-Term Memory (LSTM) network todoi:10.1109/icassp.2017.7952187 dblp:conf/icassp/DasTM17 fatcat:rpn65gmmxjc7ddewvu75d3746m