Add to ORKGAbstract: This paper is focused on on-line geometric shape recognition (Ulgen, et al., 1999) based on fuzzy techniques and backpropagation neural algorithm. We propose a new method for geometric shape recognition that consists of a hierarchical architecture implying a fuzzy classifier of angles and a multilayer neural network for training and classification of geometric shapes. Before the effective classification an on-line feature extraction process is applied. Our method examines the geometric shape as a whole in a way similar to the human recognition process. In the recognition process we have to use information that is invariant in terms of scaling, translation and rotation. The internal angles represent the relevant information relativ...
We present a neural-based learning system for object recognition in still gray-scale images. The sys...
Abstract — Moving object recognition by shape-based neural fuzzy network is proposed in this paper. ...
The past decade in computer vision research has witnessed the re-emergence of deep learning, and in ...
Abstract: This paper is focused on on-line geometric shape recognition (Ulgen et al. 1999) based on ...
Abstract: In this paper we examine the effect of shape set extension, over the architectural paramet...
We present a neural-based learning system for object recognition in still gray-scale images, The sys...
In this paper, 2-D shape recognition is done using a combination of recursive search of landmarks, l...
WOS: 000414525000010In this study, an artificial neural network model was developed to predict the g...
In this Letter, 2-D shape recognition is done using a combination of recursive search of landmarks, ...
In this Letter, 2-D shape recognition is done using a combination of recursive search of landmarks, ...
A hierarchical neural network model for the identification of arbitrary contour shapes is presented....
The paper deals with the invariant recognition of patterns, and aims at developing (i) their pulse-c...
Abstract. This paper proposes an object recognition system that is invariant to rotation, translatio...
The focus of this thesis is on the emerging technology known as Neural Networks which has recently b...
Studies on learning problems from geometry perspective have attracted an ever increasing attention i...
We present a neural-based learning system for object recognition in still gray-scale images. The sys...
Abstract — Moving object recognition by shape-based neural fuzzy network is proposed in this paper. ...
The past decade in computer vision research has witnessed the re-emergence of deep learning, and in ...
Abstract: This paper is focused on on-line geometric shape recognition (Ulgen et al. 1999) based on ...
Abstract: In this paper we examine the effect of shape set extension, over the architectural paramet...
We present a neural-based learning system for object recognition in still gray-scale images, The sys...
In this paper, 2-D shape recognition is done using a combination of recursive search of landmarks, l...
WOS: 000414525000010In this study, an artificial neural network model was developed to predict the g...
In this Letter, 2-D shape recognition is done using a combination of recursive search of landmarks, ...
In this Letter, 2-D shape recognition is done using a combination of recursive search of landmarks, ...
A hierarchical neural network model for the identification of arbitrary contour shapes is presented....
The paper deals with the invariant recognition of patterns, and aims at developing (i) their pulse-c...
Abstract. This paper proposes an object recognition system that is invariant to rotation, translatio...
The focus of this thesis is on the emerging technology known as Neural Networks which has recently b...
Studies on learning problems from geometry perspective have attracted an ever increasing attention i...
We present a neural-based learning system for object recognition in still gray-scale images. The sys...
Abstract — Moving object recognition by shape-based neural fuzzy network is proposed in this paper. ...
The past decade in computer vision research has witnessed the re-emergence of deep learning, and in ...