Over the last decade the deep neural networks are the revolutionary technique in the domain of artificial intelligence and machine learning. In the general case a deep neural network consists of multiple layers of neural units and can accomplish a deep hierarchical representation of their input data. The first layer extracts low-level features; the second layer detects higher level features, and as a result the deep neural network performs deep non-linear transformation of input data into more abstract level of representation. This paper provides an overview of deep neural networks and deep learning. Different deep learning techniques, including well-known and new approaches are discussed
The introduction of new topologies and training procedures to deep neural networks has solicited a r...
In recent years the Deep Neural Networks (DNN) has been using widely in a big range of machine lear...
In the previous tutorial, I discussed the use of deep networks to classify nonlinear data. In additi...
Over the last decade the deep neural networks are the revolutionary technique in the domain of arti...
Deep learning is a technique of machine learning in artificial intelligence area. Deep learning in a...
Deep learning is an emerging area of machine learning (ML) research. It comprises multiple hidden la...
Deep learning is an emerging area of machine learning (ML). It comprises multiple hidden layers of a...
This paper provides a comprehensive study of the latest trends and techniques in deep learning, a ra...
Abstract—The main objective of this paper is to provide a stateof- the-art survey on deep learning m...
This book will focus on the fundamentals of deep learning along with reporting on the current state-...
The unmatched learning capability of deep learning made it an attractive and indispensable technique...
This book covers both classical and modern models in deep learning. The primary focus is on the theo...
This research paper provides an overview of the development and current state of neural network tech...
Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep learning ...
Mimicking the brain is the most challenging task in the field of computer science since its origin. ...
The introduction of new topologies and training procedures to deep neural networks has solicited a r...
In recent years the Deep Neural Networks (DNN) has been using widely in a big range of machine lear...
In the previous tutorial, I discussed the use of deep networks to classify nonlinear data. In additi...
Over the last decade the deep neural networks are the revolutionary technique in the domain of arti...
Deep learning is a technique of machine learning in artificial intelligence area. Deep learning in a...
Deep learning is an emerging area of machine learning (ML) research. It comprises multiple hidden la...
Deep learning is an emerging area of machine learning (ML). It comprises multiple hidden layers of a...
This paper provides a comprehensive study of the latest trends and techniques in deep learning, a ra...
Abstract—The main objective of this paper is to provide a stateof- the-art survey on deep learning m...
This book will focus on the fundamentals of deep learning along with reporting on the current state-...
The unmatched learning capability of deep learning made it an attractive and indispensable technique...
This book covers both classical and modern models in deep learning. The primary focus is on the theo...
This research paper provides an overview of the development and current state of neural network tech...
Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep learning ...
Mimicking the brain is the most challenging task in the field of computer science since its origin. ...
The introduction of new topologies and training procedures to deep neural networks has solicited a r...
In recent years the Deep Neural Networks (DNN) has been using widely in a big range of machine lear...
In the previous tutorial, I discussed the use of deep networks to classify nonlinear data. In additi...