Abstract Deep belief networks (DBNs) are stochastic neural that can extract rich internal representations of the environment from sensory data. DBNs had a catalytic effect in triggering deep learning revolution, demonstrating for very first time feasibility unsupervised with many layers hidden neurons. These hierarchical architectures incorporate plausible biological and cognitive properties, m...

<span lang="EN-US">In deep learning, dataset plays a main role in training and getting accurate results of detection recognition objects an image. Any model needs large size to be more accurate, where improving the is one most research problems that enhancement. In this paper, image compression approach was developed reduce improve classification accuracy for trained using convolutional n...

Mental health is an important part of a successful life for person whether elderly, children, or young. Alzheimer’s fatal brain disease that severely damages the human brain, especially in elderly. One way to prevent Alzheimer's by detecting it early. The proposed research employs deep learning methodology using 3D convolutional neural network (3D CNN) has been detect at early stage. model prim...

The analytic deep prior (ADP) approach was recently introduced for the theoretical analysis of image (DIP) methods with special network architectures. In this paper, we prove that ADP is in fact equivalent to classical variational Ivanov solving ill-posed inverse problems. Besides, propose a new variant which incorporates strategy early stopping into model. For both variants, show how regulariz...

Abstract Clustering artworks is difficult for several reasons. On the one hand, recognizing meaningful patterns based on domain knowledge and visual perception extremely hard. other applying traditional clustering feature reduction techniques to highly dimensional pixel space can be ineffective. To address these issues, in this paper we propose : a DEep learning approach cLustering vIsUal artS....

The global community has recognized an increasing amount of pollutants entering oceans and other water bodies as a severe environmental, economic, social issue. In addition to prevention, one the key measures in addressing marine pollution is cleanup debris already present environments. Deployment machine learning (ML) deep (DL) techniques can automate waste removal, making process more efficie...

The introduction of Central Bank Digital Currency (CBDC) could represent a deep structural change to the financial sector, and in particular banking sector. This paper proposes Deep Neural Network (DNN) design model CBDC its potential impact on commercial banks’ deposits. proposed forecasts likelihood occurrence bank runs as function system characteristics intrinsic features CBDC. success rate ...