… In this work, we propose the first deep learning architecture for the … deep learning architecture
for the analysis of SITS data, namely DuPLO (DUal view Point deep Learning architecture …

… In order to address these gaps, we propose a novel deep learning architecture for psychometric
NLP. Our architecture incorporates provisions to address the aforementioned issues, …

… in emerging cloud computing architectures are increasingly becoming an interesting … of
deep learning architectures for emerging cloud computing architectures and provide deep …

… /LSTM layers and hidden units; learning rate; and parameters for sample selection, pooling,
and validation) were tuned to determine the architecture that achieved the lowest test error. …

… deep learning architectures, libraries which are useful and discusses various application areas
where deep learning is … overview of deep learning and its related architectures along with …

… learning model for analysis, a process we refer to as extract transform load (ETL), ready for
the deep learning … We believe this paper establishes a benchmark for deep learning on these …

… deep learning models provide good insight into improving prediction precision. Therefore,
we propose a deep learning architecture … Then, the model architecture is proposed, wherein …

… insight about deep learning through an intensive analysis of deep learning architectures and
… Also, this research work analyses recent trends in deep learning through various literatures …

… Owing to the development of deep learning [9], deep neural networks (DNNs) can be used
… For the simplicity of description, we call clustering methods with deep learning as deep …

… data and deep learning could be used to trace the evolution of architectural styles in the …
epoch classification to build a deep learning and understanding of architectural. Second, three …