Pattern Classification involves formulating a method that maps the input feature variables to
output space of binomial class. In this paper a modified fuzzy hypersphere neural network …

In data mining two important tasks involved are classification and clustering. In general, in
classification the classifier assigns a class label from a set of predefined classes to a new …

Due to the obvious inherent confusion of the information, actual analysis of it tends to be a
bit fuzzy. Fuzzy arithmetic operations are used rather than more complicated basic …

The technique of collecting important knowledge characteristics from a dataset in order to
further transform it into usable information is known as data mining. With the combined use …

Fuzzy hyper-line segment neural network (FHLSNN) is a hybrid system of fuzzy logic and
neural network and is used for pattern classification. It learns patterns in terms of n …

This is an open access book. As on date, huge volumes of data are being generated through
sensors, satellites, and simulators. Modern research on data analytics and its applications …

1.2 Objective The objective of the project was to design a portable hand held camera which
can be used to identify license plates. It was intended to simulate the design on software …

In this paper, an unsupervised feedforward Fourier fuzzy neural network (FFNN) is proposed
which is suitable for clustering of object images based on their gross shapes. This 3-layer …

A dataset is provided, and data mining extracts meaningful knowledge properties from it in
order to further transform it into meaningful information. With the combined use of statistics …

In the field of image processing, invariance refers to the properties of an image that remain
unchanged or exhibit minimal differences under transformations like rotation, scaling, or …