Md Mursalin

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Analysis of electroencephalogram (EEG) signal is crucial due to its non-stationary characteristics, which could lead the way to proper detection method for the treatment of patients with neurological abnormalities, especially for epilepsy. The performance of EEG-based epileptic seizure detection relies largely on the quality of selected features from an EEG(More)
Maximum production of crops mostly depended on proper management of weeds. In this paper we proposed an automated weed control system which can differentiate the weeds and crops from the digital image. The images were segmented to separate plant from soil. This paper demonstrates the classification of weeds and crops according to twelve extracted features.(More)
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