Now showing items 1-7 of 7

    • Assessment of Parkinson's disease severity from videos using deep architecture 

      Yin, Z.; Geraedts, V. J.; Wang, Z.; Contarino, M. F.; Dibeklioğlu, Hamdi; Gemert, J. V. (IEEE, 2021-07-26)
      Parkinson's disease (PD) diagnosis is based on clinical criteria, i.e., bradykinesia, rest tremor, rigidity, etc. Assessment of the severity of PD symptoms with clinical rating scales, however, is subject to inter-rater ...
    • Deep learning based unsupervised tissue segmentation in histopathological images 

      Köylü, Troya Çağıl (Bilkent University, 2017-11)
      In the current practice of medicine, histopathological examination of tissues is essential for cancer diagnosis. However, this task is both subject to observer variability and time consuming for pathologists. Thus, it ...
    • Deep learning for accelerated MR imaging 

      Dar, Salman Ul Hassan (Bilkent University, 2021-02)
      Magnetic resonance imaging is a non-invasive imaging modality that enables multi-contrast acquisition of an underlying anatomy, thereby supplementing mul-titude of information for diagnosis. However, prolonged scan duration ...
    • Early diagnosis of breakdown through transfer learning 

      Özbek, Seren (Bilkent University, 2019-05)
      Breakdown prediction of equipment is an essential task considering the management of resources and maintenance operations. Early diagnosis systems allow creating alerts on time for taking precautions on production. A ...
    • Real-time detection, tracking and classification of multiple moving objects in UAV videos 

      Baykara, Hüseyin Can; Bıyık, Erdem; Gül, Gamze; Onural, Deniz; Öztürk, Ahmet Safa; Yıldız, İlkay (IEEE, 2017-11)
      Unnamed Aerial Vehicles (UAVs) are becoming increasingly popular and widely used for surveillance and reconnaissance. There are some recent studies regarding moving object detection, tracking, and classification from UAV ...
    • Text mining analysis of translation, social communication and literary writing for Turkish 

      Çalışkan, Sevil (Bilkent University, 2020-12)
      Text mining is an important research area considering the increase in text generation and the need for analysis. Text mining in Turkish is still not a wellinvested research area, compared to the other languages. In this ...
    • A transfer-learning approach for accelerated MRI using deep neural networks 

      Dar, Salman Ul Hassan; Özbey, Muzaffer; Çatlı, Ahmet Burak; Çukur, Tolga (Wiley, 2020)
      Purpose: Neural networks have received recent interest for reconstruction of undersampled MR acquisitions. Ideally, network performance should be optimized by drawing the training and testing data from the same domain. In ...