Taymaz Akan--R.Farshi

Taymaz Akan--R.Farshi
Louisiana State University Health Sciences Center Shreveport · Clinical Informatics

PhD
Postdoctoral Researcher at Louisiana state university

About

31
Publications
65,365
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204
Citations
Introduction
Assistant Professor with a demonstrated history of working in the higher education industry. Skilled in C++, Matlab, Optimization, Computer Vision, and Artificial Intelligence. Strong research professional with a Doctor of Philosophy (Ph.D.) focused in Computer Engineering from Gazi University.
Additional affiliations
August 2021 - November 2021
University of Pardubice
Position
  • PostDoc Position
November 2019 - November 2019
Polytechnic Institute of Beja
Position
  • Professor
October 2019 - present
Altinbas University, Istanbul, Turkey
Position
  • Professor (Assistant)
Education
September 2013 - June 2019
Gazi University
Field of study
  • computer engineering
December 2010 - December 2012
Karadeniz Technical University
Field of study
  • Computer Science
November 2004 - December 2009
University College of Nabi Akram
Field of study
  • Computer Engineering

Publications

Publications (31)
Article
Full-text available
With technologies that have democratized the production and reproduction of information, a significant portion of daily interacted posts in social media has been infected by rumors. Despite the extensive research on rumor detection and verification, so far, the problem of calculating the spread power of rumors has not been considered. To address th...
Article
Full-text available
Human personality is significantly represented by those words which he/she uses in his/her speech or writing. As a consequence of spreading the information infrastructures (specifically the Internet and social media), human communications have reformed notably from face to face communication. Generally, Automatic Personality Prediction (or Percepti...
Article
Full-text available
Stochastic methods attempt to solve problems that cannot be solved by deterministic methods with reasonable time complexity. Optimization algorithms benefit from stochastic methods; however, they do not guarantee to obtain the optimal solution. Many optimization algorithms have been proposed for solving problems with continuous nature; nevertheless...
Article
Full-text available
Unimodal optimization algorithms can find only one global optimum solution, while multimodal ones have the ability to detect all/most existing local/global optima in the problem space. Many practical scientific and engineering optimization problems have multiple optima to be located. There are a considerable number of optimization approaches in the...
Article
Full-text available
In recent years, multi-modal optimization algorithms have attracted considerable attention, largely because many real-world problems have more than one solution. Multi-modal optimization algorithms are able to find multiple local/global optima (solutions), while unimodal optimization algorithms only find a single global optimum (solution) among the...
Preprint
Full-text available
Personality detection is an old topic in psychology and Automatic Personality Prediction (or Perception) (APP) is the automated (computationally) forecasting of the personality on different types of human generated/exchanged contents (such as text, speech, image, video). The principal objective of this study is to offer a shallow (overall) review o...
Conference Paper
Full-text available
Image retrieval is defined as finding similar or identical images in a digital image database. Various feature vectors obtained from the images are used while searching for a similar digital image. Therefore, feature extraction is one of the most important stages of content-based image retrieval (CBIR). In gray-level images, the size of the histogr...
Preprint
Full-text available
Background: Keyword extraction is a popular research topic in the field of natural language processing. Keywords are terms that describe the most relevant information in a document. The main problem that researchers are facing is how to efficiently and accurately extract the core keywords from a document. However, previous keyword extraction approa...
Article
Full-text available
Thresholding method is one of the most popular approaches for image segmentation where an objective function is defined in terms of threshold numbers and their locations in a histogram. If only a single threshold is considered, a segmented image with two classes is achieved. On the other hand, multiple classes in the output image are created with m...
Article
Full-text available
Recently, several metaheuristic optimization approaches have been developed for solving many complex problems in various areas. Most of these optimization algorithms are inspired by nature or the social behavior of some animals. However, there is no optimization algorithm which has been inspired by a game. In this paper, a novel metaheuristic optim...
Article
Full-text available
There are many techniques for conducting image analysis and pattern recognition. This papers explores a way to optimize one of these techniques—image segmentation—with the help of a novel hybrid optimization algorithm. Image segmentation is mostly used for a semantic segmentation of images, and thresholding is one the most common techniques for per...
Article
Social media is an inseparable part of our daily life where we post and share photos and media related to our life and in some cases we intend to share them between specific people. This intended and cherry picked sharing of media needs a better solution rather than simply picking users. Some social media platforms do not restrict other users from...
Code
Matlab code of "A hybrid firefly and particle swarm optimization algorithm applied to multilevel image thresholding"
Article
Full-text available
Color image quantization is a significant procedure of reducing the huge range of color values of a digital color image into a limited range. In this paper, an automated clustering of pixels and color quantization algorithm is proposed. The ideal number of representative colors is unknown beforehand in most color quantization algorithms. This is an...
Article
Color image segmentation is a fundamental challenge in the field of image analysis and pattern recognition. In this paper, a novel automated pixel clustering and color image segmentation algorithm is presented. The proposed method operates in three successive stages. In the first stage, a three-dimensional histogram of pixel colors based on the RGB...
Article
Full-text available
Multi-modal optimization algorithms are one of the most challenging issues in the field of optimization. Most real-world problems have more than one solution; therefore, the potential role of multi-modal optimization algorithms is rather significant. Multi-modal problems consider several global and local optima. Therefore, during the search process...
Article
Thresholding is one of the simplest and popular technique for segmenting images. Maximum between-class variance (Otsu’s) method is one of the well-known and widely used method in case of segmentation. Not only Otsu could be used for bi-level thresholding but also it could be extended to multi-level image thresholding. Finding the optimum threshold...
Article
Full-text available
Thresholding is an important and well-known technique that plays a major role in distinguishing the image objects from its background. In the other hand, separating the images into several different regions by determining multiple threshold values is called multilevel image thresholding. The Kapur entropy thresholding and maximum between-class vari...
Article
Full-text available
Bu çalışmada renkli görüntüler için çok seviyeli eşikleme esaslı yeni sınıflandırma algoritması önerilmiştir. Öncelikle renkli görüntülerin her bir kanalının histogramı ve arı algoritması kullanılarak eşikler tespit edilmiştir. İkinci aşamada elde edilen eşik değerleri RGB renk uzayının bölümlenmesinde kullanılmıştır. Böylece ortaya çıkan alt küple...
Article
Full-text available
In image clustering, it is desired that pixels assigned in the same class must be the same or similar. In other words, the homogeneity of a cluster must be high. In gray scale image segmentation, the specified goal is achieved by increasing the number of thresholds. However, the determination of multiple thresholds is a typical issue. Moreover, the...
Article
This paper proposes an efficient noise reduction method for gray and color images that are contaminated by salt-and-pepper noise. In the proposed method, the pixels that are more compatible with adjacent pixels are replaced with target (noisy) pixels. The algorithm is applied on noisy Lena and Mansion images that are contaminated by salt-and-pepper...
Article
Full-text available
In this paper, a multimodal firefly algorithm named the CFA (Coulomb Firefly Algorithm) has been presented based on the Coulomb’s law. The algorithm is able to find more than one optimum solution in the problem search space without requiring any additional parameter. In this proposed method, less bright fireflies would be attracted to fireflies whi...
Conference Paper
A variety of methods for images noise reduction has been developed so far. Most of them successfully remove noise but their edge preserving capabilities are weak. Therefore bilateral image filter is helpful to deal with this problem. Nevertheless, their performances depend on spatial and photometric parameters which are chosen by user. Conventional...
Article
Full-text available
In this paper, an improved multimodal optimization (MMO) algorithm,calledLSEPSO,has been proposed. LSEPSO combinedElectrostatic Particle Swarm Optimization (EPSO) algorithm and a local search method and then madesome modification onthem. It has been shown to improve global and local optima finding ability of the algorithm. This algorithm useda modi...
Conference Paper
In this paper, a novel algorithm based on Hough transform is presented for automatic detection hyperbolas in images using a modified artificial bee colony (ABC) algorithm. Hough technique is the most common solution for detecting hyperbolas in images. This method was first introduced by Richard O. Duda for detecting lines in images [1]. The disadva...

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