• Advances in Sand Cat Swarm Optimization: A Comprehensive Study 

  Anka, Ferzat; Aghayev, Nazım (Springer, 2025)

  This study provides an in-depth review and analysis of the nature-inspired Sand Cat Swarm Optimization (SCSO) algorithm. The SCSO algorithm effectively focuses on exploring solution areas inspired by sand cat hearing and ...

• Neural Architecture Search for Biomedical Image Classification: A Comparative Study Across Data Modalities 

  Kuş, Zeki; Aydın, Musa; Kiraz, Berna; Kiraz, Alper (Elsevier, 2025)

  Deep neural networks have significantly advanced medical image classification across various modalities and tasks. However, manually designing these networks is often time-consuming and suboptimal. Neural Architecture ...

• Benzetimli Tavlama ile Doğal Afetlerde Kurtarma Birimlerinin Tahsisi ve Çizelgelenmesi 

  Şimşek, Yusuf İhsan; Kuvvet, Erdinç; Sümer, Yunus; Kiraz, Berna (Institute of Electrical and Electronics Engineers Inc., 2024)

  Günümüzde dünya genelinde ve özellikle ülkemizde sıkça meydana gelen do˘gal afetler, can kaybı ve mal kaybına yol açarak ciddi sorunlara neden olmaktadır. Bu sorunların azaltılabilmesi için kurtarma ekiplerinin etkin ...

• Hyperparameter Optimization in Deep Learning-Based Object Detection of Branching and Endpoints on 2D Brain Vessel Images 

  Kaya, Samet; Kiraz, Berna; Çamurcu, Ali Yılmaz (Institute of Electrical and Electronics Engineers Inc., 2024)

  This work presents a deep learning-based object detection technique for identifying branches and endpoints in two-dimensional brain vessel images alongside its hyperparameter optimization. Although traditional image ...

• Advances in Artificial Rabbits Optimization: A Comprehensive Review 

  Anka, Ferzat; Ağaoğlu, Nazım; Nematzadeh, Sajjad; Torkamanian‑afshar, Masha (Springer, 2024)

  This study provides an in-depth review and analysis of the Artificial Rabbit Optimization (ARO) algorithm inspired by the survival strategies of rabbits. The ARO tries to find the global solution in the search space ...

• A Vector Autoregression-Based Algorithm for Dynamic Many-Objective Optimization Problems 

  Karkazan, Kalthoum; Topçuoğlu, Haluk Rahmi; Shaaban, Sahmoud (Scitepress, 2024)

  Dynamic Many-Objective Optimization Problems (DMaOPs) represent a significant challenge due to their inherent dynamism and the presence of a large number of objectives. In addressing this complexity, this paper proposes ...

• Efficiency‑Sustainability Models to Assess Blockchain Adoption Strategies with Uncertainty in the Oil and Gas Sector 

  Babaei, Ardavan; Tirkolaee, Erfan Babaee; Anka, Ferzat (Springer, 2024)

  The Oil and Gas (O&G) supply chain, vital for energy delivery, faces challenges such as excessive paperwork, limited transparency, and sustainability issues due to conventional governance methods. This study develops a ...

• A Novel Solution Approach Based on Dominance Evaluation Measure for Project Scheduling in Multi-Project Environments 

  Yousefzadeh, Hamid Reza; Tirkolaee, Erfan Babaee; Kiani, Farzad (MDPI, 2024)

  The widely recognized measure for resources called resource strength (RS) does not fully capture the resources complexity of a project. Therefore, it cannot be used as a standalone measure to distinguish the complexity ...

• Analysis of Code Similarity with Triplet Loss-Based Deep Learning System 

  Abdellatif, Abdelrahman Taha Abdeltawab; İslamoğlu, Ertuğrul; Nizam, Ali (Springer, 2024)

  Nowadays, several plagiarism detection tools based on static code features are available for code similarity detection. The application of deep learning in this domain represents an emerging area of research. This research ...

• BioNAS: Neural Architecture Search for Multiple Data Modalities in Biomedical Image Classification 

  Kuş, Zeki; Kiraz, Berna; Aydın, Musa; Kiraz, Alper (Springer, 2024)

  Neural Architecture Search (NAS) for biomedical image classification has the potential to design highly efficient and accurate networks automatically for tasks from different modalities. This paper presents BioNAS, a ...

• MedSegBench: A Comprehensive Benchmark for Medical İmage Segmentation in Diverse Data Modalities 

  Kuş, Zeki; Aydın, Musa (Nature, 2024)

  MedSegBench is a comprehensive benchmark designed to evaluate deep learning models for medical image segmentation across a wide range of modalities. It covers a wide range of modalities, including 35 datasets with over ...

• Virtual Birefringence Imaging and Histological Staining of Amyloid Deposits in Label-Free Tissue Using Autofluorescence Microscopy and Deep Learning 

  Yang, Xilin; Bai, Bijie; Zhang, Yijie; Aydın, Musa; Li, Yuzhu; Selcuk, Sahan Yoruc; Costa, Paloma Casteleiro; Guo, Zhen; Fishbein, Gregory A.; Atlan, Karine; Wallace, William Dean; Pillar, Nir; Özcan, Aydoğan (Nature, 2024)

  Systemic amyloidosis involves the deposition of misfolded proteins in organs/ tissues, leading to progressive organ dysfunction and failure. Congo red is the gold-standard chemical stain for visualizing amyloid deposits ...

• Çok Sınıflı Hücre Bölütleme için Derin Sinir Ağlarında Sınıf Ağırlıklı Cezalandırmanın Etkisi 

  Aydın, Musa; Kuş, Zeki; Kiraz, Berna; Hoşavcı, Reyhan; Kiraz, Alper (IEEE, 2024)

  Derin öğrenme ağları, birçok alanda başarılı sonuçlar vermekle birlikte karmaşıklıları sebebiyle aşırı uyum gibi problemlere sebep olmaktadır. Bu sorunu çözmek için birçok yaklaşım önerilmiş ve sınıf bazlı cezalandırma ...

• PBC-NAS: Periferik Kan Hücrelerinin Sınıflandırılması İçin Sinir Mimarisi Arama 

  Kuş, Zeki; Kiraz, Berna; Aydın, Musa; Kiraz, Alper (IEEE, 2024)

  Periferik kan hucresi (PBC) sınıflandırması, kanın bileşenlerini tanımlamak ve insan sağlığını etkileyen karmaşık ilişkilerini anlamak için temel bir araçtır. PBC’ler, eritrositler, lokositler ve trombositler gibi çeşitli ...

• Enhancing GPS Accuracy with Machine Learning: A Comparative Analysis of Algorithms 

  Zontul, Metin; Ersan, Ziya Gökalp; Yelmen, İlkay; Çevik, Taner; Anka, Ferzat; Gesoğlu, Kevser (IIETA, 2024)

  In the realm of wireless communications, the Global Positioning System (GPS), integral to Global Navigation Satellite Systems (GNSS), finds extensive applications ranging from vehicle navigation to military operations, ...

• Formation Control of Multiple Autonomous Mobile Robots Using Turkish Natural Language Processing 

  Aram, Kadir; Erdemir, Gökhan; Can, Burhanettin (MDPI, 2024)

  People use natural language to express their thoughts and wishes. As robots reside in various human environments, such as homes, offices, and hospitals, the need for human–robot communication is increasing. One of the ...

• Sahand: A Software Fault-Prediction Method Using Autoencoder Neural Network and K-Means Algorithm 

  Arasteh, Bahman; Golshan, Sahar; Shami, Shlva; Kiani, Farzad (Springer, 2024)

  Software is playing a growing role in many safety-critical applications, and software systems dependability is a major concern. Predicting faulty modules of software before the testing phase is one method for enhancing ...

• Enhancing Resolution and Contrast in Fibre Bundle-Based Fluorescence Microscopy Using Generative Adversarial Network 

  Ketabchi, Amir Mohammad; Morova, Berna; Uysallı, Yiğit; Aydın, Musa; Eren, Furkan; Bavili, Nima; Pysz, Dariusz; Buczynski, Ryszard; Kiraz, Alper (Wiley, 2024)

  Fibre bundle (FB)-based endoscopes are indispensable in biology and medical science due to their minimally invasive nature. However, resolution and contrast for fluorescence imaging are limited due to characteristic ...

• Detecting SQL Injection Attacks by Binary Gray Wolf Optimizer and Machine Learning Algorithms 

  Arasteh, Bahman; Aghaei, Babak; Farzad, Behnoud; Arasteh, Keyvan; Kiani, Farzad; Torkamanian-Afshar, Mahsa (Springer, 2024)

  SQL injection is one of the important security issues in web applications because it allows an attacker to interact with the application’s database. SQL injection attacks can be detected using machine learning algorithms. ...

• Differential Evolution-Based Neural Architecture Search for Brain Vessel Segmentation 

  Kuş, Zeki; Kiraz, Berna; Göksu, Tuğçe Koçak; Aydın, Musa; Özkan, Esra; Vural, Atay; Kiraz, Alper; Can, Burhanettin (Elsevier, 2024)

  Brain vasculature analysis is critical in developing novel treatment targets for neurodegenerative diseases. Such an accurate analysis cannot be performed manually but requires a semi-automated or fully-automated approach. ...

Daha Fazla