1. A method of constructing a convolutional neural network (CNN) for domain adaptation utilizing features extracted from multiple levels, including: selecting a CNN architecture including a plurality of convolutional layers and fully connected layers; training the CNN on a source domain data set; selecting a plurality of layers from the plurality of convolutional layers across the trained CNN; extracting features from the selected layers from the trained CNN; concatenating the extracted features to form a feature vector; connecting the feature vector to a fully connected neural network classifier; and, fine-tuning the fully connected neural network classifier from a target domain data set.