In this paper, a novel hierarchical multi-class SVM (H-MSVM) with extreme learning machine (ELM) as kernel is proposed to classify electroencephalogram (EEG) signals for epileptic seizure detection. A clinical EEG benchmark dataset having five classes, obtained from Department of Epileptology, Medical Center, University of Bonn, Germany, is considered in… (More)
In this study, an attempt is made to distinguish the normal and abnormal tissues in breast thermal images using Gabor wavelet transform. Thermograms having normal, benign and malignant tissues are considered in this study and are obtained from public online database. Segmentation of breast tissues is performed by multiplying raw image and ground truth mask.… (More)
Transfer of secret data is an important aspect in the arena of developing technology. Privacy of data is one of the major tasks required now days. In this paper, we dealt with steganographic method using randomly generated key along with raster scan, which may include horizontal or vertical pattern, access of image pixels in order to hide a plaintext in an… (More)
This paper demonstrates the superiority of energy-based features derived from the knowledge of predominant-pitch, for singing voice detection in polyphonic music over commonly used spectral features. However, such energy-based features tend to misclassify loud, pitched instruments. To provide robustness to such accompaniment we exploit the relative… (More)
is the most significant parameter in the analysis of spirometric data, it appears that this method of assessment is useful in diagnosing the pulmonary abnormalities with incomplete data and data with poor recording.