Browsing by Author "Iosifidis, Alexandros"

Now showing items 1-6 of 6

    • Data enrichment in fine-grained classification of aquatic macroinvertebrates 

      Raitoharju, Jenni; Riabchenko, Ekaterina; Meissner, Kristian; Ahmad, Iftikhar; Iosifidis, Alexandros; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)
      The types and numbers of benthic macroinverte-brates found in a water body reflect water quality. Therefore, macroinvertebrates are routinely monitored as a part of freshwater ecological quality assessment. The collected ...

    • Generalized model of biological neural networks: Progressive operational perceptrons 

      Kiranyaz, Serkan; Ince, Turker; Iosifidis, Alexandros; Gabbouj, Moncef ( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)
      Traditional Artificial Neural Networks (ANNs) such as Multi-Layer Perceptrons (MLPs) and Radial Basis Functions (RBFs) were designed to simulate biological neural networks

    • Learned vs. engineered features for fine-grained classification of aquatic macroinvertebrates 

      Riabchenko, Ekaterina; Meissner, Kristian; Ahmad, Iftikhar; Iosifidis, Alexandros; Tirronen ,Ville; ... more authors ( Institute of Electrical and Electronics Engineers Inc. , 2016 , Conference Paper)
      Aquatic macroinvertebrate biomonitoring is an efficient way of assessment of slow and subtle anthropogenic changes and their effect on water quality. It is imperative to have reliable identification and counts of the various ...

    • Learning graph affinities for spectral graph-based salient object detection 

      Aytekin, Caglar Caglar; Iosifidis, Alexandros; Kiranyaz, Serkan; Gabbouj, Moncef ( Elsevier Ltd , 2017 , Article)
      In this paper, we propose a novel method for learning graph affinities for salient object detection. First, we assume that a graph representation of an image is given with a predetermined connectivity rule and representative ...

    • Salient object segmentation based on linearly combined affinity graphs 

      Aytekin, Caglar; Iosifidis, Alexandros; Kiranyaz, Serkan; Gabbouj, Moncef ( Institute of Electrical and Electronics Engineers Inc. , 2016 , Conference Paper)
      In this paper, we propose a graph affinity learning method for a recently proposed graph-based salient object detection method, namely Extended Quantum Cuts (EQCut). We exploit the fact that the output of EQCut is ...

    • The effect of automated taxa identification errors on biological indices 

      Arje, Johanna; Karkkainen, Salme; Meissner, Kristian; Iosifidis, Alexandros; Ince, Turker; ... more authors ( Elsevier Ltd , 2017 , Article)
      In benthic macroinvertebrate biomonitoring systems, the target is to determine the status of ecosystems based on several biological indices. To increase cost-efficiency, computer-based taxa identification for image data ...