"Degree Programme in Information Technology, MSc (Tech)" - Selaus Tutkinto-ohjelman ja opintosuunnan mukaanOpinnäytteet - ylempi korkeakoulututkinto

    • 3D Semantic Mesh for Augmented Reality 

      Kong, Sehyun (2020)
      Diplomityö
      In the augmented reality (AR) or robotics applications, it is important to enhance the perception of robots or users. In many AR applications, 3D spaces of both indoor and outdoor scenes are already available but usually ...
    • Analysis of User Exploration Patterns during Scene Cuts in Omnidirectional Videos 

      Monakhov, Dmitrii (2020)
      Diplomityö
      Video content is usually represented as a sequence of scenes joined together. Two adjacent scenes can share the same semantic content, similar to filming the scene from different angles, or they can describe semantically ...
    • Camera System Characterization with Uniform Illuminate 

      Liu, Yanni (2020)
      Diplomityö
      Smartphone camera performance is increasingly important to manufacturers and users, there are many camera technologies has progressed over the years, such as sensor innovation, novel lens design and powerful AI algorithm ...
    • Cloud-Native Realization of Network Configuration Protocol 

      Bolat, Anil (2020)
      Diplomityö
      Many of the telecommunication companies aim to support Network Configuration Protocol (NETCONF) to manage their large network in cloud-native environment. The NETCONF protocol provides automation and security using permanent ...
    • Comparing clustering methods for mobile network root cause detection 

      Foucault, Thomas Etienne (2020)
      Diplomityö
      Mobile networks represent a considerable industry globally and are known to rely on robust and highly reliable systems. As a consequence, faults in the system may induce a significant loss of credibility and revenues for ...
    • Deep Neural Networks for Image Denoising 

      Huu Thanh Binh, Pham (2020)
      Diplomityö
      This master thesis introduces non-local, learning based denoising methods and proposes a new method called FlashLight CNN for denoising gray-scale images corrupted by additive white Gaussian noise (AWGN). The proposed ...
    • Design of an application for international students' participation in university development 

      Basak, Debasish (2020)
      Diplomityö
      International students are the part and parcel of a University. Their participation for the develop-ment of a university is urgently required. Normally university provide different facilities to the stu-dents. How this ...
    • Generating speech in different speaking styles using WaveNet 

      Javanmardi, Farhad (2020)
      Pro gradu -tutkielma
      Generating speech in different styles from any given style is a challenging research problem in speech technology. This topic has many applications, for example, in assistive devices and in human-computer speech interaction. ...
    • Interactive Storytelling in the Context of Large Public Spaces 

      Burova, Alisa (2020)
      Diplomityö
      Storytelling is a universal method to present information, which has been widely used throughout human history. It has been evolving into different forms, adapting to rapidly changing people’s needs and emerging visual ...
    • Investigation of RF Fingerprinting approaches in GNSS 

      Gahlawat, Sarika (2020)
      Diplomityö
      With the increase of emerging technologies, demand for location and positioning services is increasing in all domains of life. Currently there is an imperative need to protect and safeguard the authenticity and integrity ...
    • Investigations of 5G localization with positioning reference signals 

      Rahman, Meer Mizanur (2020)
      Diplomityö
      TDOA is an user-assisted or network-assisted technique, in which the user equipment calculates the time of arrival of precise positioning reference signals conveyed by mobile base stations and provides information about ...
    • Joint image demosaicing, denoising and super-resolution 

      Xing, Wenzhu Jr (2020)
      Diplomityö
    • Optimization of 2d drawings in architectural engineering and construction 

      Malysh, Konstantin (2020)
      Diplomityö
      The work of optimizing the 2d drawings in order to improve their readability and make them ready for the professional use is currently executed manually by the architectural designers, taking too much time and too many ...
    • Optimizing the Efficiency of the Data Analytics Framework Using Microservice Architecture 

      Bin Enam, Sheikh Saimul Haque Nazeef (2020)
      Diplomityö
      This thesis describes the backend of the new data analytics framework that has been designed and developed for the new reporting feature of Cloubi. Cloubi is a web application used for creating and distributing learning ...
    • Predicting Materials’ Bulk Modulus with Machine Learning 

      Hailu, Nahom Aymere (2020)
      Diplomityö
      In material science, experiments and high-throughput models often consume a large amount of calendar time and computation resources, respectively. It is, therefore, essential to consider novel methods to accelerate the ...
    • Privacy analysis of voice user interfaces 

      Yeasmin, Farida (2020)
      Diplomityö
      A voice user interface (VUI) allows a user to interact with an application or system through voice or speech commands. A voice assistant device (VAD) primarily uses VUI to communicate with the user. The popularity of VADs ...
    • Robot joint type recognition using machine learning 

      Darvishmohammadi, Bahareh (2020)
      Diplomityö
      Reconfigurable robots and mountable measurement systems face attraction due to significant changes in development of wireless networks and internet of things. This research benefits cross disciplinary viewpoints to build ...
    • Time- and frequency-asynchronous aloha for ultra narrowband communications 

      Rahman, Md Ashiqur (2020)
      Diplomityö
      A low-power wide-area network (LPWAN) is a family of wireless access technologies which consume low power and cover wide areas. They are designed to operate in both licensed and unlicensed frequency bands. Among different ...
    • Tradeoff Between Latency and Throughput in 5G Networks with Hybrid-ARQ Retransmissions 

      Gillani, Syed Hassan Uz Zaman (2020)
      Pro gradu -tutkielma
      Ultra-reliable Low Latency Communications (URLLC) is one of the key enabling technology in Fifth Generation New Radio (5G-NR), which promises to provide reliability and ultra-low latency communication link for different ...
    • Unsupervised Domain Adaptation for Audio Classification 

      Gharib, Shayan (2020)
      Pro gradu -tutkielma
      Machine learning algorithms have achieved the state-of-the-art results by utilizing deep neural networks (DNNs) across different tasks in recent years. However, the performance of DNNs suffers from mismatched conditions ...