Add to ORKGNeural networks are currently state-of-the-art technology for speech, image and other recognition tasks. This thesis describes basis properties of neural networks and their learning. The aim of this thesis was to extend Caffe framework with new learning methods and compare their performance on Cifar10 dataset. Namely RMSPROP and normalized SG
The unmatched learning capability of deep learning made it an attractive and indispensable technique...
In recent years, the machine learning technology has drawn more interest in a variety of vision task...
The thesis addresses the topic of Deep Neural Networks, in particular the methods regar- ding the fi...
Neural networks are one of the state-of-the-art models for machine learning today. One may found the...
The goal of this work is to find out the impact of approximated computing on accuracy of deep neural...
<p>This tutorial investigates various tools for designing Deep Learning Neural Networks (DLNN). Our ...
Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep learning ...
The aim of this thesis was to create a program for visualization of artificial neural networks. The ...
Artificial neural networks (ANNs) are a class of machine learning models that are loosely inspired b...
Recently, Deep Learning has brought about interesting improvements in solving computer vision proble...
This research study focuses on pattern recognition using convolutional neural network. Deep neural n...
In collaboration with BaseTIS, we explore the foundations of deep learning, focusing on image recogn...
Caffe provides multimedia scientists and practitioners with a clean and modifiable framework for sta...
This master's thesis deals with design and implementation of convolutional neural networks used in p...
The aim of the research is to compare traditional and deep learning methods in image classification ...
The unmatched learning capability of deep learning made it an attractive and indispensable technique...
In recent years, the machine learning technology has drawn more interest in a variety of vision task...
The thesis addresses the topic of Deep Neural Networks, in particular the methods regar- ding the fi...
Neural networks are one of the state-of-the-art models for machine learning today. One may found the...
The goal of this work is to find out the impact of approximated computing on accuracy of deep neural...
<p>This tutorial investigates various tools for designing Deep Learning Neural Networks (DLNN). Our ...
Since the proposal of a fast learning algorithm for deep belief networks in 2006, the deep learning ...
The aim of this thesis was to create a program for visualization of artificial neural networks. The ...
Artificial neural networks (ANNs) are a class of machine learning models that are loosely inspired b...
Recently, Deep Learning has brought about interesting improvements in solving computer vision proble...
This research study focuses on pattern recognition using convolutional neural network. Deep neural n...
In collaboration with BaseTIS, we explore the foundations of deep learning, focusing on image recogn...
Caffe provides multimedia scientists and practitioners with a clean and modifiable framework for sta...
This master's thesis deals with design and implementation of convolutional neural networks used in p...
The aim of the research is to compare traditional and deep learning methods in image classification ...
The unmatched learning capability of deep learning made it an attractive and indispensable technique...
In recent years, the machine learning technology has drawn more interest in a variety of vision task...
The thesis addresses the topic of Deep Neural Networks, in particular the methods regar- ding the fi...