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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)
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)
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)
A three-year consortium project, with members of Science Applications International Corp., University of Colorado at Boulder, Harvard University, Multimax Inc., Geophysical Institute of Israel, Western Services, and University of California at San Diego, was initiated in 2000 to improve locations and reduce uncertainties in the Middle East, North Africa,(More)
Regional S-wave amplitudes observed on recordings from the Depth of Burial (DOB) experiments conducted at the Shagan Test Site in August and September 1997 varied according to source depth (Phillips et al., 1998; Myers et al., 1999). Similar depth dependence was noted on nearfield recordings of Rg waves. These are significant observations in support of(More)
Brain tumor segmentation is a crucial step in surgical and treatment planning. Intensity-based active contour models such as gradient vector flow (GVF), magneto static active contour (MAC) and fluid vector flow (FVF) have been proposed to segment homogeneous objects/tumors in medical images. In this study, extensive experiments are done to analyze the(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)
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)