… includes a novel deep learning architecture to classify … Several approaches utilize the CNN
to learn features in the retinal … one includes convolution and pooling layer architecture. The …

… In summary, the deep learning architecture holds the advantages of 1… Although deep learning
has been successfully applied to … In this study, the efficacy of a deep learning-based CADx …

… smart resource management deep learning model. A deep learning architecture of power …
framework, a learning process with decreased time, and lower error rates. In the proposed …

… two level hierarchical deep learning architecture inspired by … recognition architecture into
root & leaf level model architectures. … deep learning architecture prevalent today. The proposed …

… We proposed a deep learning architecture with transfer learning technique that … deep
learning architecture namely VGG19, VGG16 and Inception V3 which are pre-trained architecture …

… of many architectures is often limited at some points, especially with regular architecture. In
… and noncomplex image classification architecture using deep learning based on the most …

… The experimental values of corresponding natural frequencies, for repetitive excitation of a
beam, are quite close to the values determined by our deep learning architecture. One future …

… In this paper, a dual deep learning architecture (DDLA) is used in the context of plant
speciesrecognition. The proposed method is used as a feature extraction(MobileNet + DenseNet-…

… of-the-art CNN architectures by applying the transfer learning method to diagnose COVID-19.
The results of their experiments indicated that the MobileNet architecture was the best with …

… learning phase automatically without using any human intervention. Therefore, we propose
a … based on deep learning architecture of RNN. We discuss below the RNN architecture with …