In this paper we present an hybrid approach which integrate Fuzzy C-Means (FCM) algorithms and Genetic Algorithms (GAs) to design an optimal classifier for the specific classification problem. This integration allows automatic generation of an classifier system, with an optimized subset of features, from a database of examples. The generated classifier strongly outperform the classic FCM algori...

In this paper we propose a wet lab algorithm for prediction of radiation fog by DNA computing. The concept of DNA computing is essentially exploited for generating the classifier algorithm in the wet lab. The classifier is based on a new concept of similarity based fuzzy reasoning suitable for wet lab implementation. This new concept of similarity based fuzzy reasoning is different from convent...

Face Detection is the process of determining the face location, size and number. It can be considered as a classification problem in the sense that a given image region can be classified as face or non-face classes. In this paper, we propose a method based on skin color segmentation and classification with Fuzzy Information Granulation (FIG) for robust and fast face detection in color images. T...

The multiple classifier system (MCS) is an effective automatic classification method, useful in connection with remote sensing analysis techniques. Combining MSC with induced fuzzy topology enables a decomposition of image classes. This fuzzy topological MCS then provides a new and improved approach to classification. The basic classification methods discussed in this paper include maximum like...