DIGITAL IMAGE PROCESSING USING CONVOLUTIONAL NEURAL NETWORKS

摘要

According to an example, a digital image may be processed by an ensemble of convolutional neural networks (CNNs) to classify objects in the digital image. For each CNN, a candidate architecture and candidate parameters may be selected to build a plurality of CNNs. Once it is determined that a predetermined number of CNNs, each having different values for the selected candidate parameters, meet a validation threshold, an ensemble of CNNs may be generated from the predetermined number of CNNs. The predictions from the ensemble of CNNs may then be aggregated to accurately classify the objects in the digital image.