Some mature findings in person recognition research restrict their use cases for dealing with near frontal face poses under controlled environments conditions. Such special pose and environment conditions can be accepted if imposed as a requirement for security applications, but they are not reasonable constraints when dealing with personal collections. In this paper a person recognition approa...

The magniication exponents occuring in adaptive map formation algorithms like Kohonen's self-organizing feature map deviate for the information theoretically optimal value = 1 as well as from the values which optimize, e.g., the mean square distortion error (= 1=3 for one-dimensional maps). At the same time, models for categorical perception such as the \perceptual magnet" eeect which are based...

The self-organizing feature maps developed by Kohonen appear to capture some of the advantages of the natural systems on which they are based. A summary of the operation of this form of artificial neural network is presented. It was concluded that the primary benefits of using self-organizing feature maps result from their adaptability and plasticity while most problems are largely caused by th...

-Classification, a data mining task is an effective method to classify the data in the process of Knowledge Data Discovery. Classification method algorithms are widely used in medical field to classify the medical data for diagnosis. Feature Selection increases the accuracy of the Classifier because it eliminates irrelevant attributes. This paper analyzes the performance of neural network class...

In this paper we describe a novel use of a multi-layer Kohonen self-organizing feature map (MLKSFM) for spoken language identification (LID). A normalized, segment-based input feature vector is used in order to maintain the temporal information of speech signal. The LID is performed by using different system configurations of the MLKSFM. Compared with a baseline PPRLM system, our novel system i...

A self-organizing neural network for sequence classification called SARDNET is described and analyzed experimentally. SARDNET extends the Kohonen Feature Map architecture with activation retention and decay in order to create unique distributed response patterns for different sequences. SARDNET yields extremely dense yet descriptive representations of sequential input in very few training itera...

The explosive growth of digital image collections on the Web sites is calling for an efficient and intelligent method of browsing, searching, and retrieving images. In this article, an artificial neural network (ANN)-based approach is proposed to explore a promising solution to the Web image retrieval (IR). Compared with other image retrieval methods, this new approach has the following charact...

-This paper proposes and describes a hierarchical self-organizing neural network for range image segmentation. The multilayer self-organizing feature map (MLSOFM), which is an extension of the traditional (singlelayer ) self-organizing feature map ( SOFM) is seen to alleviate the shortcomings of the latter in the context of range image segmentation. The problem of range image segmentation is fo...

[1] Despite its wide applications as a tool for feature extraction, the Self-Organizing Map (SOM) remains a black box to most meteorologists and oceanographers. This paper evaluates the feature extraction performance of the SOM by using artificial data representative of known patterns. The SOM is shown to extract the patterns of a linear progressive sine wave. Sensitivity studies are performed ...

This paper presents a biologically inspired method for the navigation of autonomous mobile systems. The method calculates the way from a current position to a target position using one-dimensional 360° images, taken at these positions. The correlations between the two images are generated by using a modified version of Kohonen’s self-organizing feature map. The direction to the target position ...