Browsing by Author "Mammeri, Oumeima"

Now showing 1 - 1 of 1
  • No Thumbnail Available
    Item
    Semantic segmentation
    (Université Larbi Ben M'hidi Oum El Bouaghi, 2022) Mammeri, Oumeima; Medkour, Romaissa; Chibani, Meriem
    Image semantic segmentation is more and more being of interest for computer vision and machine learning researchers. Many applications on the rise need accurate and efficient segmentation mechanisms: autonomous driving, indoor navigation, and even virtual or augmented reality systems to name a few. It is a building block for scene understanding by classifying all pixels of an image in a dense way; it is then possible to build abstract representations focusing on the objects and their shapes. In this project, our work exploits a convolutional neural network (CNN) architecture "unet" for semantic segmentation; the choice of this architecture is due to its phenomenal success, it can solve the most complex problems in deep learning. It is a particularly effective tool for many types of images. Our model is trained on the Oxford-iiit pet dataset.