Jiang, Z., Key Laboratory of Groundwater Resources and Environment, Ministry of Education, College of Environment and Resources, Jilin University, Changchun, 130021, China, CSIRO Land and Water, Locked Bag 2, Glen Osmond, SA 5064, Australia; Mallants, D., CSIRO Land and Water, Locked Bag 2, Glen Osmond, SA 5064, Australia; Peeters, L., CSIRO Mineral Resources, Locked Bag 2, Glen Osmond, SA 5064, Australia; Gao, L., CSIRO Land and Water, Locked Bag 2, Glen Osmond, SA 5064, Australia; Soerensen, C., CSIRO Mineral Resources, Locked Bag 2, Glen Osmond, SA 5064, Australia; Mariethoz, G., University of Lausanne, Faculty of Geosciences and Environment, Institute of Earth Surface Dynamics, Lausanne, Switzerland
Recommended Citation:
Jiang Z.,Mallants D.,Peeters L.,et al. High-resolution paleovalley classification from airborne electromagnetic imaging and deep neural network training using digital elevation model data[J]. Hydrology and Earth System Sciences,2019-01-01,23(6)