Masoud Moradi

Eastern Mediterranean University · Department of Electrical and Electronic Engineering

Alzheimer’s disease is a kind of neurological disorder that directly impacts the memory of a patient. Structural magnetic resonance imaging (sMRI) is an effective representation for the diagnosis of neurodegenerative diseases. Deep learning strategies, such as convolutional neural networks (CNNs), require an enormous amount of data to generalize th...

Mild cognitive impairment (MCI) conversion prediction is a vital challenge in the area of Alzheimer’s disease (AD) as it could determine possible treatment pathways for AD patients. In this work, we presented a robust MCI conversion prediction framework based on the 3D-Zernike Moment (3D-ZM) method that generates statistical features (e.g., shape,...

SAR generates high-resolution images irrespective of any weather condition and solar illumination. Feature-level fusion increases the dimensionally of feature space as well as feature redundancy brought by correlation among the features. In this paper, we propose a technique to select the most discriminative feature extraction techniques based on F...

In this paper, a new approach for improving the classification of different kinds of ground vehicles from moving stationary target acquisition and recognition images is proposed. Pseudo Zernike moments are used for feature extraction due to its capability of being scale, rotation, and translation invariant. To benefit from the diversities of region...

In this paper, a novel approach for selection of relevant features in SAR-ATR is proposed. The main concern of all studies in this filed is the accuracy. For this reason, many researchers have worked on feature extraction phase. Just a few studies focus on feature selection stage. The goal of working on feature selection is twofold. Firstly, the di...

Abstract - This study proposes a new approach for improving the accuracy of high-dimensional pattern recognition problem of Alzheimer’s Disease (AD). The proposed method uses information from three-dimensional Magnetic Resonance Imaging (MRI) brain data with 2D slices in three orthogonal directions. It includes the calculation of Fisher Criterion b...

In this paper four feature extraction techniques are utilized to extract features from Synthetic Aperture Radar images namely as Radial Harmonic Fourier Moment, Local Binary Pattern, Haar Wavelet and Radon Transform. Holdout, 2-fold and 10-fold cross validation techniques are used for classification of images by using Support Vector Machine classif...