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This paper presents three techniques of plants classification based on their leaf shape the SVM-BDT, PNN and Fourier moment technique for solving multiclass problems. All the three techniques have been applied to a database of 1600 leaf shapes from 32 different classes, where most of the classes have 50 leaf samples of similar kind. In the proposed work(More)
Multiclass brain tumor classification is performed by using a diversified dataset of 428 post-contrast T1-weighted MR images from 55 patients. These images are of primary brain tumors namely astrocytoma (AS), glioblastoma multiforme (GBM), childhood tumor-medulloblastoma (MED), meningioma (MEN), secondary tumor-metastatic (MET), and normal regions (NR).(More)
BACKGROUND Congenital nephrotic syndrome arises from a defect in the glomerular filtration barrier that permits the unrestricted passage of protein across the barrier, resulting in proteinuria, hypoalbuminaemia, and severe oedema. While most cases are due to mutations in one of five genes, in up to 15% of cases, a genetic cause is not identified. We(More)
A mobile ad hoc network is a multihop wireless network with dynamically and frequently changing topology. The power, energy and bandwidth constraint of these self operating and self organized systems has made routing a challenging problem. Number of routing protocols has been developed to find routes with minimum control overhead and network resources.(More)
Image data has distinct regions of different importance. This property of image data has extensively been used to develop partial encryption techniques, but it is still unnoticed for total encryption. Providing similar security level to data of varied significance consumes more computational resources. This necessitates the development of an encryption(More)
The present study is conducted to assist radiologists in marking tumor boundaries and in decision making process for multiclass classification of brain tumors. Primary brain tumors and secondary brain tumors along with normal regions are segmented by Gradient Vector Flow (GVF)-a boundary based technique. GVF is a user interactive model for extracting tumor(More)
In this paper the capability of Relevance Vector Machines to perform multiclass classification has been illustrated. It has been demonstrated how faults in an analog circuit can be diagnosed by analyzing these faults as a multiclass machine learning problem. A simple first order Op-amp RC circuit validates our methodology which can be further applied to(More)