Mohammad Reza Ahmadzadeh

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Optimization plays a critical role in human modern life. Nowadays, optimization is used in many aspects of human modern life including engineering, medicine, agriculture and economy. Due to the growing number of optimization problems and their growing complexity, we need to improve and develop theoretical and practical optimization methods. Stochastic(More)
This paper deals with a recently proposed non-parametric approach to camera calibration, which is applicable to any type of sensor design. Currently, no relative quantitative performance data is available for this method. This paper addresses this issue, by providing a comprehensive evaluation with respect to the standard planar calibration technique in the(More)
In this paper we present the Dempster-Shafer theory as a framework within which the results of a Bayesian network classifier and a fuzzy logic-based classifier are combined to produce a better final classification. We deal with the case when the two original classifiers use different classes for the outcome. The problem of different classes is solved by(More)
Particle swarm optimization (PSO) is an optimization algorithm that has received much attention in recent years. PSO is a simple and computationally inexpensive algorithm inspired by social behavior of bird flocks and fish schools. However, PSO suffers from premature convergence, especially in high dimensional multimodal functions. To improve PSO(More)
Motion analysis or quality assessment of human sperm cell is great important for clinical applications of male infertility. Sperm tracking is quite complex due to cell collision, occlusion and missed detection. The aim of this study is simultaneous tracking of multiple human sperm cells. In the first step in this research, the frame difference algorithm is(More)
Clusters of Microcalcifications and masses are the signs of breast cancer. They have different shapes and sizes. Globally, clusters and masses have different frequency characteristics. Due to small size of microcalcifications and high intensity of them with compared to their neighbour pixels, microcalcifications correspond to high-frequency components of(More)
This paper presents a new method to classify vehicles with resolving vehicle occlusions in traffic images. Moving objects are detected in an image sequence using a probability-based background extraction and object segmentation algorithm. The partially occluded vehicles are detected by evaluating the convexity of the moving objects and split by the(More)
Musical staff detection and removal is one of the most important preprocessing steps of an Optical Music Recognition (OMR) system. This paper proposes a new method for detecting and restoring staff lines from global information of music sheets. First of all the location of staff lines is determined. Therefore, music staff is sliced. The staff line segments(More)
The aim of this article is to propose an intelligent electrocardiogram classifier. The classifier is similar to probabilistic neural networks. In these networks, a user needs to set some parameters optionally. Improper selections may decrease the performance drastically. The proposed method needs no optional parameter settings and all required parameters(More)