• 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. ...

• A Bioinspired Test Generation Method Using Discretized and Modified Bat Optimization Algorithm 

  Arasteh, Bahman; Arasteh, Keyvan; Kiani, Farzad; Sefati, Seyed Salar; Fratu, Octavian; Halunga, Simona; Tirkolaee, Erfan Babaee (MDPI, 2024)

  The process of software development is incomplete without software testing. Software testing expenses account for almost half of all development expenses. The automation of the testing process is seen to be a technique ...

• Triplet MAML for Few-shot Classification Problems 

  Gülcü, Ayla; Özkan, İsmail Taha Samed; Kuş, Zeki; Karakuş, Osman Furkan (Springer, 2023)

  In this study, we propose a TripletMAML algorithm as an extension to Model-Agnostic Meta-Learning (MAML) which is the most widely-used optimization-based meta-learning algorithm. We approach MAML from a metric-learning ...

• Radar Placement Optimization Based on Adaptive Multi-Objective Meta-Heuristics 

  Tema, Emrah Y.; Sahmoud, Shaaban; Kiraz, Berna (Elsevier, 2024)

  Airspace surveillance is a significant issue for many countries to control and manage their airspace. The number of radars used and their coverage rate are the main issues to consider in this case. Therefore, this paper ...

• Classification of Fruit Images as Fresh and Rotten Using Convolutional Neural Networks 

  Göksu, Tuğçe; Kaya, Zeliha; Sahmoud, Shaaban (IEEE, 2023)

  Many fruits are produced all over the world, and the fruits produced are sent abroad and sold in a relatively short time in many countries. During the period between collection and sale, the fruits may undergo various types ...

• What to predict from Twitter Data? 

  Salemdeeb, Mohammed; Sahmoud, Shaaban (IEEE, 2023)

  In the last decade, Twitter data has become one of the most valuable research sources for many areas including health, marketing, security, and politics. Researchers prefer Twitter data since it is completely public and ...

• A Unified Framework for Multi-Language Sentiment Analysis 

  Abdellatif, Abdelrahman; Sahmoud, Shaaban; Nizam, Ali (IEEE, 2023)

  The unified framework for multi-language sentiment analysis is a vital aspect of understanding customer opinions, emotions, and feedback. This paper presents a unified framework to increase the performance of the ...

• Protecting Android Devices from Malware Attacks: A State-of-the-Art Report of Concepts, Modern Learning Models and Challenges 

  Bayazıt, Esra Çalık; Şahingöz, Özgür Koray; Doğan, Buket (IEEE, 2023)

  Advancements in microelectronics have increased the popularity of mobile devices like cellphones, tablets, e-readers, and PDAs. Android, with its open-source platform, broad device support, customizability, and integration ...

• BaDENAS: Retina Damar Segmentasyonu için Bayes Tabanlı Sinir Mimarisi Arama 

  Kuş, Zeki; Kiraz, Berna (IEEE, 2023)

  Retinal damar segmentasyonu, retinal görüntülerin analizi için önemli bir görevdir ve göz hastalıklarının teşhisinde ve tedavisinde kullanılan etkili bir araçtır. Damar segmentasyonunu otomatik hale getiren U-Net gibi derin ...

• Hücre Canlılığı Tespitinde Yapay Öğrenme Yaklaşımları 

  Kaya, Zeliha; Kuş, Zeki; Kiraz, Berna; Uludağ, Gönül (IEEE, 2023)

  Hücre canlılığı, kök hücre tedavileri, kanser tedavileri, estetik ve kozmetik gibi klinik araştırmalarda önemli yer tutmaktadır. Doğru tedavi ve yaklaşımın uygulanabilmesi için alınan örnekteki toplam hücre canlılık oranı ...

• Deep Learning With Class-Level Abstract Syntax Tree and Code Histories for Detecting Code Modification Requirements 

  Büyük, O.O.; Nizam, Ali (Elsevier, 2023)

  Improving code quality is one of the most significant issues in the software industry. Deep learning is an emerging area of research for detecting code smells and addressing refactoring requirements. The aim of this study ...

• Evolutionary Architecture Optimization for Retinal Vessel Segmentation 

  Kuş, Zeki; Kiraz, Berna (IEEE, 2023)

  Retinal vessel segmentation (RVS) is crucial in medical image analysis as it helps identify and monitor retinal diseases. Deep learning approaches have shown promising results for RVS, but designing optimal neural network ...

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