Browsing by Subject "Computational costs"

Now showing items 1-5 of 5

    • Infrared Versus Visible Image Matching for Multispectral Face Recognition 

      Syed W.W.; Al-Maadeed, Somaya ( Springer , 2020 , Conference Paper)
      Multispectral face recognition has been an interesting area of research where images obtained from different bands are matched. There are many face image datasets available which contain infrared and visible images. In ...

    • K-Subspaces Quantization for Approximate Nearest Neighbor Search 

      Ozan E.C.; Kiranyaz, Mustafa Serkan; Gabbouj M. ( IEEE Computer Society , 2016 , Article)
      Approximate Nearest Neighbor (ANN) search has become a popular approach for performing fast and efficient retrieval on very large-scale datasets in recent years, as the size and dimension of data grow continuously. In this ...

    • MEdge-Chain: Leveraging Edge Computing and Blockchain for Efficient Medical Data Exchange 

      Abdellatif A.A.; Samara L.; Mohamed A.; Erbad A.; Chiasserini C.F.; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2021 , Article)
      Medical data exchange between diverse e-health entities can lead to a better healthcare quality, improving the response time in emergency conditions, and a more accurate control of critical medical events (e.g., national ...

    • Nonlocal damage modelling in clay/epoxy nanocomposites using a multiscale approach 

      Silani, Mohammad; Talebi, Hossein; Hamouda, Abdel Magid; Rabczuk, Timon ( Elsevier , 2016 , Article)
      This study proposed a concurrent multiscale method to model damage in clay/epoxy nanocomposites. The method uses a nonlocal damage formulation to regularize the damage model. The multiscale method used, is based on the ...

    • Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks 

      Ince, Turker; Kiranyaz, Serkan; Eren, Levent; Askar, Murat; Gabbouj, Moncef ( Institute of Electrical and Electronics Engineers Inc. , 2016 , Article)
      Early detection of the motor faults is essential and artificial neural networks are widely used for this purpose. The typical systems usually encapsulate two distinct blocks: feature extraction and classification. Such ...