Add to ORKGThis paper proposes a new invariant feature-space system based in the log-polar image representation and Self-Organizing Maps (SOMs). The image representation used, which is inspired by the structure of the human retina, allows data reduction and helps recognize image contents at different scales and orientations. Each object class is represented by a single prototype image, thus allowing classes to be mapped into just a few neurons within the SOM. This paper also presents some object recognition experiments, using controlled and generic images, incorporating invariances by training and by feature space. Results have shown the viability of using log-polar images and SOM in classification tasks in a way relatively independent of orientation ...
Heidemann G, Saalbach A, Ritter H. Semi-automatic acquisition and labeling of image data using SOMs....
In this paper, we present a hierarchical self-organiziuig map applying to scaling and rotation invar...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...
This paper presents an approach for content-based image retrieval, which combines GH-SOM (Growing Hi...
Abstract- This work proposes a model of the development of visual object recognition, based on the c...
Abstract. This paper is a review of works about the use of the log-polar image model for pattern rec...
Self-organising? feature maps (SOFM) are an important tool to visualize high-dimensional data as a t...
The problem of computing object-based visual representations can be construed as the development of ...
A classifier with self-organizing maps (SOM) as feature detectors resembles the biological visual sy...
Abstract- Se1f-organizing feature maps (SOFM) are an important tool to visualize high-dimensional da...
A review of recent development of the self-organising map (SOM) for applications related to data map...
This paper presents a new model for capturing spatial information for object categorization with bag...
Convolutional neural network (CNN)-based works show that learned features, rather than handpicked fe...
Abstract. We present a modification of the well-known Self-Organizing Map (SOM) in which we incremen...
The paper presents a novel artificial neural network type, which is based on the learning rule of th...
Heidemann G, Saalbach A, Ritter H. Semi-automatic acquisition and labeling of image data using SOMs....
In this paper, we present a hierarchical self-organiziuig map applying to scaling and rotation invar...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...
This paper presents an approach for content-based image retrieval, which combines GH-SOM (Growing Hi...
Abstract- This work proposes a model of the development of visual object recognition, based on the c...
Abstract. This paper is a review of works about the use of the log-polar image model for pattern rec...
Self-organising? feature maps (SOFM) are an important tool to visualize high-dimensional data as a t...
The problem of computing object-based visual representations can be construed as the development of ...
A classifier with self-organizing maps (SOM) as feature detectors resembles the biological visual sy...
Abstract- Se1f-organizing feature maps (SOFM) are an important tool to visualize high-dimensional da...
A review of recent development of the self-organising map (SOM) for applications related to data map...
This paper presents a new model for capturing spatial information for object categorization with bag...
Convolutional neural network (CNN)-based works show that learned features, rather than handpicked fe...
Abstract. We present a modification of the well-known Self-Organizing Map (SOM) in which we incremen...
The paper presents a novel artificial neural network type, which is based on the learning rule of th...
Heidemann G, Saalbach A, Ritter H. Semi-automatic acquisition and labeling of image data using SOMs....
In this paper, we present a hierarchical self-organiziuig map applying to scaling and rotation invar...
The Self-Organizing Map (SOM) is a neural network algorithm, which uses a competitive learning techn...