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A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj
A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj
Electronic Theses and Dissertations
Electroencephalogram (EEG) has been used in a wide array of applications to study mental disorders. Due to its non-invasive and low-cost features, EEG has become a viable instrument in Brain-Computer Interfaces (BCI). These BCI systems integrate user's neural features with robotic machines to perform tasks. However, due to EEG signals being highly dynamic in nature, BCI systems are still unstable and prone to unanticipated noise interference. An important application of this technology is to help facilitate the lives of the tetraplegic through assimilating human brain impulses and converting them into mechanical motion. However, BCI systems are remarkably challenging to implement …
Enhanced Breast Cancer Classification With Automatic Thresholding Using Support Vector Machine And Harris Corner Detection, Mohammad Taheri
Enhanced Breast Cancer Classification With Automatic Thresholding Using Support Vector Machine And Harris Corner Detection, Mohammad Taheri
Electronic Theses and Dissertations
Image classification and extracting the characteristics of a tumor are the powerful tools in medical science. In case of breast cancer medical treatment, the breast cancer classification methods can be used to classify input images as benign and malignant classes for better diagnoses and earlier detection with breast tumors. However, classification process can be challenging because of the existence of noise in the images, and complicated structures of the image. Manual classification of the images is timeconsuming, and need to be done only by medical experts. Hence using an automated medical image classification tool is useful and necessary. In addition, …