Add to ORKGTranslation, rotation (in plane) and scale invariant pattern recognition is a high-order recognition problem encountered frequently in real-world applications. But neither traditional image process/pattern recognition algorithms nor artificial neural networks have yet provided satisfactory solutions for this problem after years of study. Recent research has shown that a higher order neural networks (HONNs) of order three with built-in invariances can effectively achieve invariant pattern recognition.Master of Engineerin
Invariant object recognition is maybe the most basic and fundamental property of our visual system. ...
In this paper, we discuss a methodology for applying feedforward networks to problems of invariant p...
A new approach to recognition of images using invariant features based on higher-order spectra is pr...
Translation, rotation (in plane) and scale invariant pattern recognition is a high-order recognition...
Abstract: In this paper, a modification for the high-order neural network (HONN) is presented. Third...
In this paper, a modification for the high-order neural network (HONN) is presented. Third order net...
The state-of-the-art in pattern recognition for such applications as automatic target recognition an...
We introduce a group-theoretic model of invariant pattern recognition, the Group Representation Netw...
This thesis is concerned with study of high order neural networks for character recognition. The goa...
A hierarchical neural network model for the identification of arbitrary contour shapes is presented....
A second-order architecture is presented here for translation, rotation and scale invariant processi...
When recognizing patterns or objects, our visual system can easily separate what kind of pattern is ...
A neural network model is proposed to achieve invariant pattern recognition to binary inputs based o...
In this document we review and compare some of the classical and modern techniques for solving the p...
This research is concerned with the application of neural network techniques to the problems of clas...
Invariant object recognition is maybe the most basic and fundamental property of our visual system. ...
In this paper, we discuss a methodology for applying feedforward networks to problems of invariant p...
A new approach to recognition of images using invariant features based on higher-order spectra is pr...
Translation, rotation (in plane) and scale invariant pattern recognition is a high-order recognition...
Abstract: In this paper, a modification for the high-order neural network (HONN) is presented. Third...
In this paper, a modification for the high-order neural network (HONN) is presented. Third order net...
The state-of-the-art in pattern recognition for such applications as automatic target recognition an...
We introduce a group-theoretic model of invariant pattern recognition, the Group Representation Netw...
This thesis is concerned with study of high order neural networks for character recognition. The goa...
A hierarchical neural network model for the identification of arbitrary contour shapes is presented....
A second-order architecture is presented here for translation, rotation and scale invariant processi...
When recognizing patterns or objects, our visual system can easily separate what kind of pattern is ...
A neural network model is proposed to achieve invariant pattern recognition to binary inputs based o...
In this document we review and compare some of the classical and modern techniques for solving the p...
This research is concerned with the application of neural network techniques to the problems of clas...
Invariant object recognition is maybe the most basic and fundamental property of our visual system. ...
In this paper, we discuss a methodology for applying feedforward networks to problems of invariant p...
A new approach to recognition of images using invariant features based on higher-order spectra is pr...