Arama Sonuçları

Listeleniyor 1 - 4 / 4
  • Yayın
    Automated cell nucleus detection for large-volume electron microscopy of neural tissue
    (IEEE, 2014-04-29) Tek, Faik Boray; Kroeger, Thorben; Hamprecht, Fred A.; Mikula, Shawn
    Volumetric electron microscopy techniques, such as serial block-face electron microscopy (SBEM), generate massive amounts of image data that are used for reconstructing neural circuits. Typically, this requires time-intensive manual annotation of cells and their connections. To facilitate this analysis, we study the problem of automated detection of cell nuclei in a new SBEM dataset that contains cerebral cortex, white matter, and striatum from an adult mouse brain. The dataset was manually annotated to identify the locations of all 3309 cell nuclei in the volume. We make both dataset and annotations available here. Using a hybrid approach that combines interactive learning, morphological processing, and object level feature classification, we demonstrate automated detection of cell nuclei at 92.4% recall and 95.1% precision. These algorithms are not RAM-limited and can scale to arbitrarily large datasets.
  • Yayın
    Thermo-microstretch elastic bodies and plane waves
    (IOP PUBLISHING LTD, 2011) İnan, Esin; Kırış, Ahmet
    In the present work, vibration problems of rectangular plates are considered for the determination of upper bounds to the unknown microstretch material properties. The frequencies are obtained by extending the Ritz method to this case. The analysis shows that some additional frequencies characterizing the microstretch effects appear among the classical frequencies. Furthermore, by the increasing values of the microstretch constants, the additional frequencies disappear and only the classical frequencies remain in the spectrum. Considering this phenomenon, an optimization problem is established for the identification of the upper bounds of microstretch elastic constants. In the second part of the work, thermal effects are considered and several theories are discussed. Finally, propagation of the plane waves is investigated.
  • Yayın
    Real time electrocardiogram identification with multi-modal machine learning algorithms
    (Springer International Publishing AG, 2018) Waili, Tuerxun; Nor, Rizal Mohd; Sidek, Khairul Azami; Rahman, Abdul Wahab Bin Abdul; Güven, Gökhan
    Weaknesses in conventional identification technologies such as identification cards, badges and RFID tags prompts attention to biometric form of identification. Biometrics like voice, brain signal and finger print are unique human traits that can be used for identification. In this paper we present an identification system based on Electrocardiogram (heart signal). There is a considerable number of research in the past with high accuracy for identification , however, most ignore the practical time required to identify an individual. In this study, we explored a more practical approach in identification by reducing the number of time required for identification. We explore ways to identity a person within 3-4 s using just 5 heart beats. We extracted few reliable features from each QRS complexes, combined effort of three algorithms to achieve 96% accuracy. This approach is more suitable and practical in real time applications where time for identification is important.
  • Yayın
    Transforming tourism experience: AI-based smart travel platform
    (Association for Computing Machinery, 2023) Yöndem, Meltem Turhan; Özçelik, Şuayb Talha; Caetano, Inés; Figueiredo, José; Alves, Patrícia; Marreiros, Goreti; Bahtiyar, Hüseyin; Yüksel, Eda; Perales, Fernando
    In this paper, we propose the development of a novel personalized tourism platform incorporating artificial intelligence (AI) and augmented reality (AR) technologies to enhance the smart tourism experience. The platform utilizes various data sources, including travel history, user activity, and personality assessments, combined with machine learning algorithms to generate tailored travel recommendations for individual users. We implemented fundamental requirements for the platform: secure user identification using blockchain technology and provision of personalized services based on user interests and preferences. By addressing these requirements, the platform aims to increase tourist satisfaction and improve the efficiency of the tourism industry. In collaboration with various universities and companies, this multinational project aims to create a versatile platform that can seamlessly integrate new smart tourism units, providing an engaging, educational, and enjoyable experience for users.