… This paper presents a novel deep learning technique for intrusion … deep autoencoder (NDAE)
for unsupervised feature learning. Furthermore, we also propose our novel deep learning …

… This work highlights the utility of deep learning approaches to … learning approaches afford
the opportunity to rapidly and inexpensively explore vast chemical spaces in silico. Our deep …

… deep learning based approach for developing such an efficient and flexible NIDS. We use
Self-taught Learning (STL), a deep learning … We present the performance of our approach and …

… In this paper, deep neural network (DNN), a type of deep learning model is explored to …
generated over the years through static and dynamic approaches. This type of study facilitates to …

… of using machine learning (ML) and deep learning (DL) techniques. Both ML and DL come
under the big umbrella of artificial intelligence (AI) and aim at learning useful information from …

… , deep learning along with the theory behind SdA were briefly introduced. Test result shows
that a deep learning approach … over the typical classification approach that requires careful (…

… [58], and these show that deep learning models have superior … In this paper, we explore
a deep learning approach with … We propose a deep learning approach with a SAE model for …

… learning approach to image segmentation, deep learning approach to image segmentation,
deep learning architectures, typical approaches for implementing deep learning …

… Deep learning has become an area of … deep learning approach that is widely used for solving
complex problems. It overcomes the limitations of traditional machine learning approaches. …

… deep learning approach to automatically generate natural looking speech animation that
synchronizes to input speech. Our approach uses … Our deep learning approach enjoys several …