… representation, and lack of contextual … increased dramatically to 120 min. Meanwhile,
the running time during the training stage also increased to 20 min due to the deeper network …

… of highly complex data has substantially increased their … is to find the features that best
represent input data reconstructed, … the CNN based on classes spectral, contextual, and spatial …

… representative deep neural networks, convolutional neural … Deep convolutional neural
networks (CNN), as a contextual-… adversarial learning to enhance the capability of deep learning …

… Performance was further improved by considering the state-of… Thus, spatial information is
maintained to provide contextual … show that deep convolutional neural networks perform well in …

… of different methods could be improved with the use of a standard … of RS images, by using
contextual information of the … η is the learning rate, and x ( i ) and y ( i ) represent, respectively, …

… and, therefore, a better representation of the data can be … that fully convolutional neural
networks can yield improved … path which complements the contextual classification. The detail by …

… improved the classification accuracy of urban ground targets. It … The spatial, textural, and
contextual features extracted by … a fixed-size image as the representation of an image object (…

… in relation to deep convolutional neural networks (CNN), due … , contextual-based), Multi-scale
CNN applied to land cover (… demonstrated that greatly increased classification accuracy for …

… information brought by the increased spatial resolution and … to rely on deep neural networks
for presenting the contextual … background, which is represented using black color. The fine …

… of contextual information to feature representation and object … We present a detailed
study of these contextual issues in … different enhancement methods for different categories to …