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Doktor Öğretim Üyesi Taymaz AkanMühendislik Fakültesi/Yazılım Mühendisliği Bölümü/Yazılım Mühendisliği Pr. /
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Multilevel image thresholding with multimodal optimization

Taymaz Akan

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 multilevel thresholding. Otsu and Kapur's procedures have been conventional steps for defining objective functions. Nevertheless, the fundamental problem with thresholding techniques is the determination of threshold numbers, which must be selected by ...Daha fazlası

Makale 2021 Multimedia Tools and Applications80 ( 10 ) , pp. 1 - 15289 120 Görüntülenme Süresiz Ambargo
Erişime Açık

Text‑based automatic personality prediction: a bibliographic review

Taymaz Akan

Personality detection is an old topic in psychology and automatic personality prediction (or perception) (APP) is the automated (computationally) forecasting of the personality on diferent types of human generated/exchanged contents (such as text, speech, image, and video). The principal objective of this study is to ofer a shallow (overall) review of natural language processing approaches on APP since 2010. With the advent of deep learning and following it transfer-learning and pre-trained model in NLP, APP research area has been a hot topic, so in this review, methods are categorized into th ...Daha fazlası

Makale 2022 Journal of Computational Social Science5 ( 2 ) , pp. 1 - 1593 94 Görüntülenme
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Brain magnetic resonance image (MRI) segmentation using multimodal optimization

Taymaz Akan

One of the highly focused areas in the medical science community is segmenting tumors from brain magnetic resonance imaging (MRI). The diagnosis of malignant tumors at an early stage is necessary to provide treatment for patients. The patient’s prognosis will improve if it is detected early. Medical experts use a manual method of segmentation when making a diagnosis of brain tumors. This study proposes a new approach to simplify and automate this process. In recent research, multi-level segmentation has been widely used in medical image analysis, and the effectiveness and precision of the segm ...Daha fazlası

Makale 2024 Multimedia Tools and Applications 0 Görüntülenme
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Image retrieval with SNN-based multi-level thresholding

Taymaz Akan

Image retrieval is defined as indexing 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. However, processing all pixels of the images requires costly algorithms. In addition, it is a possible issue that the images used in retrieval approaches are of different sizes. For this reason, pixel-level operations are insufficient when comparing images. Therefore, it requires vectorial structures that represent images. The process of obtaining these vectorial structures is called feature extrac ...Daha fazlası

Makale 2022 Gümüşhane Üniversitesi Fen Bilimleri Dergisi 0 Görüntülenme
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BinBRO: Binary Battle Royale Optimizer algorithm

Taymaz Akan

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, they are unable to solve discrete or binary problems. Adaptation and use of continuous optimization algorithms for solving discrete problems have gained growing popularity in recent decades. In this paper, the binary version of a recently proposed ...Daha fazlası

Makale 2022 Expert Systems With Applications195 119 Görüntülenme Süresiz Ambargo
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Multi-modal Battle Royale optimizer

Taymaz Akan

Multimodal optimization poses a challenging problem in the field of optimization as it entails the discovery of multiple local and global optima, unlike unimodal optimization, which seeks a single global solution. In recent years, the significance of addressing multimodal optimization challenges has grown due to the real-world complexity of many problems. While numerous optimization methods are available for unimodal problems, multimodal optimization techniques have garnered increased attention. However, these approaches often grapple with a common issue: the determination of the niching param ...Daha fazlası

Makale 2024 CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 12 Görüntülenme
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Battle royale optimizer for multilevel image thresholding

Taymaz Akan

Image segmentation, the process of partitioning an image into meaningful regions, is a fundamental step in image processing, crucial for applications like computer vision, medical imaging, and object recognition. Image segmentation is an essential step of image processing that directly affects its success. Among the methods used for image segmentation, histogram-based thresholding is prevalent. Two well-known approaches to histogram-based thresholding are Otsu’s and Kapur’s methods in gray images that maximize the between-class variance and the entropy measure, respectively. Both techniques we ...Daha fazlası

Makale 2024 Journal of Supercomputing80 ( 4 ) , pp. 5 - 5340 33 Görüntülenme
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A multi-modal bacterial foraging optimization algorithm

Taymaz Akan

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 set of the solutions. Niche-based multi-modal optimization approaches have been widely used for solving multi-modal problems. These methods require a predefined niching parameter but estimating the proper value of the niching parameter is challengin ...Daha fazlası

Makale 2021 Journal of Ambient Intelligence and Humanized Computing12 ( 11 ) , pp. 1 - 10049 125 Görüntülenme Süresiz Ambargo
Süresiz Ambargo

Battle royale optimizer for training multi-layer perceptron

Taymaz Akan

Artificial neural network (ANN) is one of the most successful tools in machine learning. The success of ANN mostly depends on its architecture and learning procedure. Multi-layer perceptron (MLP) is a popular form of ANN. Moreover, backpropagation is a well-known gradient-based approach for training MLP. Gradient-based search approaches have a low convergence rate therefore, they may get stuck in local minima, which may lead to performance degradation. Training the MLP is accomplished based on minimizing the total network error, which can be considered as an optimization problem. Stochastic op ...Daha fazlası

Makale 2021 Evolving Systems13 ( 4 ) , pp. 5 - 575 111 Görüntülenme Süresiz Ambargo
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A multimodal butterfly optimization using fitness-distance balance

Taymaz Akan

Due to the multimodal nature of real-world optimization problems, in recent years, there has been a great interest in multi-modal optimization algorithms. Multimodal optimization problems involve identifying multiple local/global optima. Niching techniques have been widely used to tackle multi-modal optimization problems. Most of the existing niching methods either require predefined niching parameters or extra information about the problem space. This paper presents a novel multimodal algorithm based on Butterfly Optimization Algorithm, which is constructed using the Fitness-Distance Balance ...Daha fazlası

Makale 2023 SOFT COMPUTING27 ( 23 ) , pp. 1 - 17922 20 Görüntülenme Süresiz Ambargo
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Multi-circle Detection Using Multimodal Optimization

Taymaz Akan

Object and shape detection in digital image were one of the hot topic over the last two decades. Especially automatic multi circle detection has received more attention over last years. Hough transform (HT) is a well-known and most popular method for lines and circles detection. However, HT has huge computational complexity expense. This paper proposed a new successful heuristic method to reduce computation time and improve the speed of HT for circle detection. In this proposed method the edges information of the image is obtained by means of Robert edge detection. Then, multimodal particle sw ...Daha fazlası

Kitap Bölümü 2023 Studies in Computational Intelligence1069 , pp. 1 - 209 105 Görüntülenme
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MOBRO: multi-objective battle royale optimizer

Taymaz Akan

Battle Royale Optimizer (BRO) is a recently proposed optimization algorithm that has added a new category named game-based optimization algorithms to the existing categorization of optimization algorithms. Both continuous and binary versions of this algorithm have already been proposed. Generally, optimization problems can be divided into single-objective and multi-objective problems. Although BRO has successfully solved single-objective optimization problems, no multi-objective version has been proposed for it yet. This gap motivated us to design and implement the multi-objective version of B ...Daha fazlası

Makale 2023 JOURNAL OF SUPERCOMPUTING 38 Görüntülenme Süresiz Ambargo
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