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Biomedical Signals and Images

Neuroscience

Industrial Visual Inspection
Content-Based
Image Retrieval

Methods

  • Supervised, semisupervised and unsupervised classification
  • Statistical methods for data analysis
  • Machine learning (neural networks, support vector machine, etc.)
  • Kernel-based methods and support vector machines
  • Domain adaptation and active learning algorithms
  • Multidimensional signal processing
  • 2D and 3D image processing
  • Data fusion

Applications

  • Remote sensing
  • Biomedical Signals and Images
  • Neuroscience
  • Industrial Visual Inspection
  • Others

Biomedical Signals and Images

  • Analysis of retina images for diseases detection and mapping
  • Analisys of MRI and fMRI images
  • Analysis of TAC images
  • Analysis of ECG and ECoG signals
  • Analysis of EEG signals
  • Development of Brain Computer Interface (BCI) systems
Neuroscience

  • Analysis of fMRI signals
  • Analysis of EEG and MEG signals
  • Fusion between EEG, MEG and fMRI data
  • Pattern recognition for cognitive analysis

Laboratory of Functional Neuroimaging, CIMeC.

This activity is developed in cooperation with CIMeC – Centro interdipartimentale Mente/Cervello (Center for Mind/Brain Sciences), University of Trento.

Industrial Visual Inspection

  • Fig Quality Assessment

This activity is developed in cooperation with the Vision-Image Processing and Pattern Recognition Laboratory, Süleyman Demirel University, Isparta, Turkey.

Content-Based Image Retrieval (CBIR)

  • Image Feature Extraction for CBIR problems
  • Fast content-based Image Retrieval
  • Relevance Feedback Driven by Active Learning