• Makine Öğrenme Yöntemleri Ve Kelime Kümesi Tekniği İle İstenmeyen E-Posta / E-Posta Sınıflaması 

      Şahin, Esra (Fen Bilimleri Enstitüsü, 2018)
      Nowadays, we frequently use e-mails, which is one of the communication channels, in electronic environment. It plays an important role in our lives because of many reasons such as personal communications, business-focused ...
    • Mikroservisler için Verimli Yerleştirme Alternatiflerinin Türetilmesi 

      Karabey Aksakallı, Işıl (Fen Bilimleri Enstitüsü, 2021)
      Microservice architecture is a popular approach that relies on modular software components that are loosely coupled, operate with a single functionality that can be independently deployed and communicate with each other ...
    • Mobil Uygulamaların Evriminde Kalitenin Gelişimi 

      Gezici, Bahar (Fen Bilimleri Enstitüsü, 2018)
      Mobile applications are becoming complex software systems as they rapidly evolve and grow constantly to meet user requirements. However, satisfying these requirements may lead to poor design choices known as ‘antipatterns’ ...
    • Modelıng Of The Ionosphere's Dısturbance Usıng Deep Learnıng Technıques 

      Abrı Zangabad, Rahem (Fen Bilimleri Enstitüsü, 2021-09-14)
      The ionosphere drives an essential role in the atmosphere and earth. Solar flares due to coronal mass ejection, seismic movements, and geomagnetic activity cause deviations in the ionosphere. The main parameter for ...
    • Multi-Scheduling Technıque for Real-Time Systems on Embedded Multi-Core Processors 

      Yaşar, Abdulkadir (Fen Bilimleri Enstitüsü, 2014)
      This thesis introduces Multi-scheduling method for Multi-core hardware platforms without running heterogeneous operating systems concurrently. In this technique, there are two schedulers in single operating system. One of ...
    • Multilevel Sentiment Analysis in Arabic 

      NASSAR, AHMED (Fen Bilimleri Enstitüsü, 2017-08-24)
      Sentiment analysis has a great necessity to classify sentences like review, news, blog, etc. in order to hold the overall sentiment (i.e. negative, positive or neutral) embedded in them. The vast majority of studies focused ...
    • Neural Dependency Parsıng For Turkısh 

      Tuç, Salih (Fen Bilimleri Enstitüsü, 2020-06)
      Dependency Parsing is the task of finding the grammatical structure of a sentence by identify- ing syntactic and semantic relationships between words. The current accuracy of the depen- dency parsers is still not satisfying ...
    • Neural Text Normalization for Turkish Social Media 

      Göker, Sinan (Fen Bilimleri Enstitüsü, 2018)
      Social media has become a rich data source for natural language processing tasks with its worldwide use; however, it is hard to process social media data directly in language studies due to its unformatted nature. Text ...
    • Neural Word Embeddings for Sentiment Analysis 

      Naderalvojoud, Behzad (Fen Bilimleri Enstitüsü, 2020)
      Most pre-trained word embeddings are achieved from context-based learning algorithms trained over a large text corpus. This leads to learning similar vectors for words that share most of their contexts, while expressing ...
    • Omuz Egzersizlerinin RGB-D Verisi Kullanılarak Gerçek Zamanlı Kestirimi İçin Sanal Egzersiz Sistemi 

      Ulutaş, Volkan (Fen Bilimleri Enstitüsü, 2019-09-30)
      Shoulder pain and discomfort are common and serious problems. Shoulder treatment benefits from a structured and repetitive program. In traditional physical rehabilitation programs, patients frequently perform exercises ...
    • Online Time Delay and Disturbance Compensation for Linear Non Minimum Phase Systems 

      Demirtaş, Özlem (Fen Bilimleri Enstitüsü, 2021)
      Disturbances often occur in real systems and this has a negative effect on system stability and performance. In the past, a number of remedies have been proposed to enhance the stability and performance characteristics ...
    • Open Domain Factoid Question Answering Systems 

      Soleimanian Gharehchopogh, Farhad (Fen Bilimleri Enstitüsü, 2015)
      Question Answering (QA) is a field of Artificial Intelligence (AI) and Information Retrieval (IR) and Natural Language Processing (NLP), and leads to generating systems that answer to questions natural language in open and ...
    • Otomatik Duygu Sözlüğü Çevirimi ve Duygu Analizinde Kullanımı 

      Uçan, Alaettin (Fen Bilimleri Enstitüsü, 2014)
      People want to decide in their daily and seasonal activities by referring other people's emotions, experiences or opinions. This tendency also means transfer of experience and expansion of communal memory. For instance, ...
    • Otomatik Duygu Sözlüğü Geliştirilmesi ve Haberlerin Duygu Analizi 

      Sağlam, Fatih (Fen Bilimleri Enstitüsü, 2019)
      The level reached by mass media today, with respect to informing the society, raising awareness, affecting opinions, and even mobilizing masses, is impressive. Being mass communication tools, mainstream news media produces ...
    • Parallelization Analysis of ECO Tracking Algorithm on GPUs 

      Taygan, Uğur (Fen Bilimleri Enstitüsü, 2020-06)
      Object tracking is a very popular area in image processing. Its popularity comes from the variety of its application areas. It is used for security and surveillance, autonomous vehicles, human-machine interaction, traffic ...
    • Path Plannıng Usıng Heurıstıc Algorıthm in Dynamıc Envıronment 

      Elmi, Zahra (Fen Bilimleri Enstitüsü, 2019-08-30)
      Navigation of mobile robots and autonomous vehicles is one of the important issues in computer and control sciences. Path planning and obstacle avoidance are current topics of navigational challenges for mobile robots and ...
    • Producing Synthetic Person Images with Deep Generative Artificial Neural Networks 

      Günel, Mehmet (Fen Bilimleri Enstitüsü, 2018)
      Producing synthetic person images has wide variety of applications including digital photo sharing and editing, visual surveillance, fashion and art design and human interactive autonomous machines, among others. In the ...
    • Recognıtıon Of Human Interactıons Usıng Hıstogram Of Sequences 

      Çavent, Aytaç (Fen Bilimleri Enstitüsü, 2018-10-08)
      In recent years, many techniques have been proposed for recognition of the human interactions in the computer vision literature. To recognize human interactions, spatial and temporal descriptors have been used together. ...
    • Recognızıng Human Interactıons In Stıll Images 

      Tanışık, Gökhan (Fen Bilimleri Enstitüsü, 2020)
      Recognizing human interactions in still images is quite a challenging problem since compared to videos, there is only a glimpse of interaction in a single image. In this thesis, we explore the role of two components that ...
    • Reinforcement Learning based Adaptive Access Class Barring for RAN Slicing in 5G Networks 

      Turan, Ali (Fen Bilimleri Enstitüsü, 2021-09-28)
      Machine-to-Machine (M2M) communication is one of the major drivers of 5G networks as M2M traffic might soon surpass Human-to-Human (H2H) traffic. Network slicing is a promising technique for supporting M2M traffic on 5G ...