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BIOGRAPHY Shankararaman Ramakrishnan received the B.E. (Hons.) degree in Electrical and Electronics Engineering from the Birla Institute of Technology and Science – Pilani, India in 2006. He is currently a M.S. candidate at Stanford University in the Department of Aeronautics and Astronautics and is also a member of the Global Positioning System laboratory(More)
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 work, an attempt has been made to analyze the cyclostationarity of surface electromyography (sEMG) signals recorded during dynamic contraction of biceps brachii muscle. Twenty five healthy adult volunteers have participated in this study. The recorded signals are preprocessed and segmented into three zones, namely, non-fatigue zone, first muscle(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)