Multichannel information processing from a diverse range of channel information is highly
time-and space-complex owing to the variety and enormity of underlying data. Most of the …

In this information era, processing of noisy and noise-free images and multimedia data for
faithful analysis and retrieval of useful information has assumed utmost importance. One of …

Segmentation is targeted to partition an image into distinct regions comprising pixels having
similar attributes. In the context of image analysis and interpretation, these partitioned …

Segmentation of the different feature based data in a dataset is a challenging proposition in
the image processing community. There exist different techniques to solve this problem …

The paper describes a self supervised parallel self organizing neural network (PSONN)
architecture for true color image segmentation. The proposed architecture is a parallel …

The parallel self-organizing neural network (PSONN) architecture uses bilevel sigmoidal
activation functions for the purpose of extraction of embedded objects from pure color noisy …

This chapter presents a self-supervised learning network in a quantum environment, named
a “quantum parallel bidirectional self-organizing neural network (QPBDSONN) architecture” …

A multilayer self organizing neural neural network (MLSONN) architecture for binary object
extraction, guided by a beta activation function and characterized by backpropagation of …

This paper proposes a new technique for the problem of color image segmentation using
GrabCut. GrabCut is considered as one of the semi-automatic segmentation techniques …

Most of the image preprocessing techniques by existing neighborhood neural networks,
suffer from the problem of false classification of the image features. This is mainly due to the …