… We designed several experiments, with the candidate … We expect that using such a validation
set would provide a good estimation … In addition, it uses a global average pooling layer as a …

… uses an ensemble of different convolutional neural network (… work in modality classification:
we have designed and trained … For efficient classifier training, we reduced the dimensionality …

… the results of an ensemble of five weak models. For demonstration purposes we report the
… ImageNet classification with deep convolutional neural networks. Communications of the …

… potential to effectively perform supervised classification. In … a SVM and a conventional deep
neural network. After that, in [22]… The convolution layer uses different filters to extract features …

… a powerful general-purpose image classification system able to … ensembles based on the
fusion of classifiers. Our main objective is to design a method that is both robust and effective …

… Hair removal is the purpose of the preprocessing stage. Dermoscopy … Neural network
ensembles are effective only when the individual … for image classification,” in Proc. …

… [12], decision trees [13], ensemble learning [14], support vector … In this paper, we introduce
a simple yet effective … guide the architecture design, Auto-CNN uses the gradient descent …

… land image processing—often called remote sensing image … Ensembles of learning algorithms
have been effectively used … for classification purposes is better than just using the image …

… representation approaches for cloud image classification: hand-… A successful approach to
overcome the high variance … apply a model average ensemble to the designed CNN model in …

… The purpose of this research is to design an NN ensemble … Hitherto, efforts have been
made to design ensemble by … NNs can produce a good ensemble that distribute errors over …