Add to ORKGNeural networks have been massively used, during these last years, as a powerful tool in the field of vision and pattern recognition. Notwithstanding this, there are some tasks that the unique use of a neural network fails or seems to be ineffective. One way to solve these problems is coupling an artificial neural network with a symbolic system. The aim of this paper is to show a neurosymbolic hybrid system for classifying and reconstructing images formed by bidimensional geometrical figures. 1
A neural network model, called an FBF network, is proposed for automatic parallel separation of mult...
The paper presents a novel artificial neural network type, which is based on the learning rule of th...
A preprocessor based on ( I computational model of simple cells in the mammalian primary visual cort...
There are several methods for categorizing images, the most of which are statistical, geometric, mod...
Abstract. Comparative study of the recognition of nonsemantic geometrical figures by the human subje...
The focus of this thesis is on the emerging technology known as Neural Networks which has recently b...
A new approach is proposed for the integration of neural networks (NN) with machine learning techniq...
We developed an intelligent agent for image processing in this paper. The description of image proc...
An artificial modular system to get an anatomical objects classification is presented. The study ana...
We approach the integration between symbolic and subsymbolic processing within a hybrid model of vis...
This paper presents a methodology for integrating connectionist and symbolic approaches to 2D image ...
This book presents a first generation of artificial brains, using vision as sample application. An o...
In this paper an artificial modular system applied to object classification in brain MR images is pr...
An approach to setting the architecture and the initial weights of an artificial neural network for ...
In fine art, especially painting, humans have mastered the skill to create unique visual experiences...
A neural network model, called an FBF network, is proposed for automatic parallel separation of mult...
The paper presents a novel artificial neural network type, which is based on the learning rule of th...
A preprocessor based on ( I computational model of simple cells in the mammalian primary visual cort...
There are several methods for categorizing images, the most of which are statistical, geometric, mod...
Abstract. Comparative study of the recognition of nonsemantic geometrical figures by the human subje...
The focus of this thesis is on the emerging technology known as Neural Networks which has recently b...
A new approach is proposed for the integration of neural networks (NN) with machine learning techniq...
We developed an intelligent agent for image processing in this paper. The description of image proc...
An artificial modular system to get an anatomical objects classification is presented. The study ana...
We approach the integration between symbolic and subsymbolic processing within a hybrid model of vis...
This paper presents a methodology for integrating connectionist and symbolic approaches to 2D image ...
This book presents a first generation of artificial brains, using vision as sample application. An o...
In this paper an artificial modular system applied to object classification in brain MR images is pr...
An approach to setting the architecture and the initial weights of an artificial neural network for ...
In fine art, especially painting, humans have mastered the skill to create unique visual experiences...
A neural network model, called an FBF network, is proposed for automatic parallel separation of mult...
The paper presents a novel artificial neural network type, which is based on the learning rule of th...
A preprocessor based on ( I computational model of simple cells in the mammalian primary visual cort...