The performance of a pattern recognition system is dependent on, among other things, an appropriate data-preprocessing technique, In this paper, we describe a method to evaluate the performance of a variety of these techniques for the problem of odour classification using an array of gas sensors, also referred to as an electronic nose. Four experimental odour databases with different complexiti...

This paper addresses the problem of Bangla basic character recognition. Multi-font Bangla character recognition has not been attempted previously. Twenty popular Bangla fonts have been used for the purpose of character recognition. A novel feature extraction scheme based on the digital curvelet transform is proposed. The curvelet transform, although heavily utilized in various areas of image pr...

We propose a mixed language query disambiguation approach by using co-occurrence information from monolingual data only. A mixed language query consists of words in a primary language and a secondary language. Our method translates the query into monolingual queries in either language. Two novel features for disambiguation, namely contextual word voting and 1-best contextual word, are introduce...

This paper presents a new appearance-based place recognition system for topological localization. The method uses a panoramic vision system to sense the environment. Color images are classified in real-time based on nearest-neighbor learning, image histogram matching, and a simple voting scheme. The system has been evaluated with eight cross-sequence tests in four unmodified environments, three...

In this paper, we discuss properties of the Knack system which is designed as a testbed for experimenting memory retrieval and organization in Case-Based Reasoning. Methods used for retrieval and indexing are based on mathematically sound techniques developed in classification, clustering and decision analysis. Retrieval is done using decision theoretic methods such as voting k nearest neighbor...

k-Nearest Neighbor (k-NN) is one of the classification algorithms which becomes top 10 in data mining. k-NN simple and easy to apply. However, results are greatly influenced by scale input. All its attributes considered equally important Euclidean distance, but inappropriate with relevance each attribute. Thus, it makes decreased. Some more or less or, fact, irrelevant determining results. To o...

High-dimensional data are by their very nature often difficult to handle by conventional machine-learning algorithms, which is usually characterized as an aspect of the curse of dimensionality. However, it was shown that some of the arising high-dimensional phenomena can be exploited to increase algorithm accuracy. One such phenomenon is hubness, which refers to the emergence of hubs in high-di...

Classification learning applies to a wide range of tasks, from diagnosis and troubleshooting to pattern recognition and keyword assignment. Many methods have been used to build classification systems, including artificial neural networks, rule-based expert systems (both hand-built and inductively learned), fuzzy rule systems, memorybased and case-based systems and nearest neighbor systems, gene...

some applications are critical and must designed Fault Tolerant System. Usually Voting Algorithm is one of the principle elements of a Fault Tolerant System. Two kinds of voting algorithm are used in most applications, they are majority voting algorithm and weighted average algorithm these algorithms have some problems. Majority confronts with the problem of threshold limits and voter of weight...

some applications are critical and must designed Fault Tolerant System. Usually Voting Algorithm is one of the principle elements of a Fault Tolerant System. Two kinds of voting algorithm are used in most applications, they are majority voting algorithm and weighted average algorithm these algorithms have some problems. Majority confronts with the problem of threshold limits and voter of weight...