… of feature extraction that used in a deep learning technique … of actual literatures on feature
extraction methods since past … study and analysis in the feature extraction field became very …

… Deep learning can automatically learn feature representation from big data, … feature
extraction first, and then expands frequently used deep learning methods in text feature extraction …

… layers and evolving to learn features of the image in the deeper layers, resulting in … feature
of an images is extracted using convolution neural network using the concept of deep learning…

… (CNNs), the feature extraction operation has become more … to extract features also for the
other parts of a deep learning model. The selection of a suitable network for feature extraction …

… impact of automatic feature extraction and classification used in deep learning such as CNN…
image, and feature based traditional MLPs. CNN with automatic feature extraction was firstly …

… In this paper, we aim to combine both feature selection and feature extraction methods with
deep learning techniques to learn more representative characteristics from gene expression …

… machine learning algorithms for classification using feature extraction ability of deep
neural network architectures and we are inspired by transfer learning methodology to this. …

… In this article, a CNN is designed for feature extraction and damage localization task at once.
Typically, a convolutional network may consist of multiple convolutional layers. Furthermore…

… feature extraction methods have been investigated so far. Indeed, feature extraction is a crucial
step in machine learning … , we can distinct handcrafted and deep learning features. In this …

… This paper proposes a novel deep learning-based feature extraction framework for building
security rules. We show how deep autoencoders can be used to transform the space of …