Mandava Rajeswari

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This work presents two novel approaches to determine optimum growing multi-experts network (GMN) structure. The first method called direct method deals with expertise domain and levels in connection with local experts. The growing neural gas (GNG) algorithm is used to cluster the local experts. The concept of error distribution is used to apportion error(More)
This paper presents a framework for soccer event detection through collaborative analysis of the textual, visual and aural modalities. The basic notion is to decompose a match video into smaller segments until ultimately the desired eventful segment is identified. Simple features are considered namely the minute-by-minute reports from sports websites (i.e.,(More)
A new trend of problem formulation for image segmentation is to use multiobjective optimization approach in its decision making process. Multiobjective formulations are realistic models for many complex optimization problems. In many real-life problems, objectives under consideration conflict with each other, and optimizing a particular solution with(More)
In this paper, a novel approach to automatically segment the optic disc contour using the center point of an optic disc candidate is proposed. The optic disc segmentation algorithm consists of 2 stages. The first stage involves the removal of blood vessels that obscure the optic disc. The blood vessel structures are detected using morphological operations.(More)
This paper introduces an approach to perform segmentation of regions in computed tomography (CT) images that exhibit intra-region intensity variations and at the same time have similar intensity distributions with surrounding/adjacent regions. In this work, we adapt a feature computed from wavelet transform called wavelet energy to represent the region(More)
This paper presents a comparative study of Bayesian belief network structure learning algorithms with a view to identify a suitable algorithm for modeling the contextual relations among objects typically found in natural imagery. Four popular structure learning algorithms are compared: two constraint-based algorithms (PC proposed by Spirtes and Glymour and(More)
In recent years, the machine learning community has witnessed a tremendous growth in the development of kernel-based learning algorithms. However, the performance of this class of algorithms greatly depends on the choice of the kernel function. Kernel function implicitly represents the inner product between a pair of points of a dataset in a higher(More)
Automatic brain MRI image segmentation is a challenging problem and received significant attention in the field of medical image processing. In this paper, we present a new dynamic clustering algorithm based on the Harmony Search (HS) hybridized with Fuzzy C-means called DCHS to automatically segment the brain MRI image in an intelligent manner. In this(More)
Using the lectin-concanavalin-A, the tryptophan fluorescence as a function of pH was studied. The pH dependent, fluorescence intensity changes were significantly higher when excited at 305 nm, than when irradiated at 280nm. Only one tryptophanyl per monomer of concanavalin-A was available for oxidation by N-bromosuccinimide in the dimeric form at pH 4·9; no(More)