Add to ORKGWe investigate the use of a morphological neural network to improve the performance of information retrieval systems. A morphological neural network is a neural network based on lattice algebra that is capable of solving decision boundary problems. The morphological neural network structure is one that theoretically can be easily applied to information retrieval. In this paper we propose a new information retrieval system based on morphological neural networks and present experimental results comparing it against other proven models
We describe a self-organizing framework for the generation of a network useful in content-based retr...
International audienceIn the last ten years, Convolutional Neural Networks (CNNs) have formed the ba...
A model of a neural system is presented that achieves feature based retrieval. It establishes the pr...
A morphological neural network is generally defined as a type of artificial neural network that perf...
Morphological neural networks (MNNs) are a class of artificial neural networks whose operations can ...
This paper deals with using of the neural networks in information retrieval. There are studied and d...
Neural networks and particularly Deep learning have been comparatively little studied from the theor...
Author presents concept and historical outline of the development of the artificial neuronal network...
A recent "third wave'' of neural network (NN) approaches now delivers state-of-the-art performance i...
Morphological neural networks (MNNs) can be characterized as a class of artificial neural networks t...
This book highlights the ability of neural networks (NNs) to be excellent pattern matchers and their...
The article discusses the artificial neurone networks as the way of representation of the knowledge ...
Neural networks represent a promising approach to problems, which exact algorithmic solution is unkn...
Artificial Intelligence Lab, Department of MIS, University of ArizonaInformation retrieval using pro...
Mathematical morphology is a theory and technique applied to collect features like geometric and top...
We describe a self-organizing framework for the generation of a network useful in content-based retr...
International audienceIn the last ten years, Convolutional Neural Networks (CNNs) have formed the ba...
A model of a neural system is presented that achieves feature based retrieval. It establishes the pr...
A morphological neural network is generally defined as a type of artificial neural network that perf...
Morphological neural networks (MNNs) are a class of artificial neural networks whose operations can ...
This paper deals with using of the neural networks in information retrieval. There are studied and d...
Neural networks and particularly Deep learning have been comparatively little studied from the theor...
Author presents concept and historical outline of the development of the artificial neuronal network...
A recent "third wave'' of neural network (NN) approaches now delivers state-of-the-art performance i...
Morphological neural networks (MNNs) can be characterized as a class of artificial neural networks t...
This book highlights the ability of neural networks (NNs) to be excellent pattern matchers and their...
The article discusses the artificial neurone networks as the way of representation of the knowledge ...
Neural networks represent a promising approach to problems, which exact algorithmic solution is unkn...
Artificial Intelligence Lab, Department of MIS, University of ArizonaInformation retrieval using pro...
Mathematical morphology is a theory and technique applied to collect features like geometric and top...
We describe a self-organizing framework for the generation of a network useful in content-based retr...
International audienceIn the last ten years, Convolutional Neural Networks (CNNs) have formed the ba...
A model of a neural system is presented that achieves feature based retrieval. It establishes the pr...