Enviaments recents

  • The impact of segmentation on the accuracy and sensitivity of a melanoma classifier based on skin lesion images 

    Burdick, Jack; Marques, Oge; Romero-Lopez, Adrià; Giró Nieto, Xavier; Weinthal, Janet (2017)
    Comunicació de congrés
    Accés obert
  • Distributed training strategies for a computer vision deep learning algorithm on a distributed GPU cluster 

    Campos Camunez, Victor; Sastre, Francesc; Yagües, Maurici; Bellver, Míriam; Giró Nieto, Xavier; Torres Viñals, Jordi (Elsevier, 2017)
    Comunicació de congrés
    Accés obert
    Deep learning algorithms base their success on building high learning capacity models with millions of parameters that are tuned in a data-driven fashion. These models are trained by processing millions of examples, so ...
  • Spatio-temporal road detection from aerial imagery using CNNs 

    Luque, Belen; Morros Rubió, Josep Ramon; Ruiz Hidalgo, Javier (SCITEPRESS, 2017)
    Text en actes de congrés
    Accés obert
    The main goal of this paper is to detect roads from aerial imagery recorded by drones. To achieve this, we propose a modification of SegNet, a deep fully convolutional neural network for image segmentation. In order to ...
  • Morphological interpolation for texture coding 

    Casas Pla, Josep Ramon; Salembier Clairon, Philippe Jean; Torres Urgell, Lluís (. S.N., 1995)
    Text en actes de congrés
    Accés obert
    In this paper a new morphological interpolation technique is presented. It is applied to the coding of the smooth (primary) component in a sketch-based image compression approach for very low bit-rates. The interpolation ...
  • Motion region overlapping for segmentation-based video coding 

    Pardàs Feliu, Montse; Salembier Clairon, Philippe Jean; Gonzalez, Benito (. S.N., 1994)
    Text en actes de congrés
    Accés obert
    In object-based video coding systems, the scenes are described in terms of three dimensional objects, which can be coded as textures and contours. However, in order to achieve high compression ratios, the redundancy in the ...
  • Segmentation-based multi-scale edge extraction to measure the persistence of features in unorganized point clouds 

    Bazazian, Dena; Casas Pla, Josep Ramon; Ruiz Hidalgo, Javier (2017)
    Text en actes de congrés
    Accés obert
    Edge extraction has attracted a lot of attention in computer vision. The accuracy of extracting edges in point clouds can be a significant asset for a variety of engineering scenarios. To address these issues, we propose ...
  • Connected operators based on region-tree pruning strategies 

    Salembier Clairon, Philippe Jean; Garrido Ostermann, Luis (Barcelona, 2000)
    Comunicació de congrés
    Accés obert
    This paper discusses region-based representations useful to create connected operators. The filtering approach involves three steps: 1) a region tree representation of the input image is constructed; 2) the simplification ...
  • A new approach to active contours for tracking 

    Pardàs Feliu, Montse; Sayrol Clols, Elisa (Institute of Electrical and Electronics Engineers (IEEE), 2000)
    Text en actes de congrés
    Accés obert
    This paper addresses the application of active contours or snakes for robust tracking of contours. Conventional snake approaches to tracking initialize the current frame snake with the snake obtained in the previous frame ...
  • A morphological approach for segmentation and tracking of human faces 

    Marqués Acosta, Fernando; Vilaplana Besler, Verónica (Barcelona, 2000)
    Comunicació de congrés
    Accés obert
    A new technique for segmenting and tracking human faces in video sequences is presented. The technique relies on morphological tools such as using connected operators to extract the connected component that more likely ...
  • 3D convolutional neural networks for brain tumor segmentation 

    Casamitjana Díaz, Adrià; Puch Giner, Santi; Aduriz Saiz, Asier; Sayrol Clols, Elisa; Vilaplana Besler, Verónica (2016)
    Comunicació de congrés
    Accés restringit per política de l'editorial
    This paper presents our work on applying 3D Convolutional Networks for brain tumor segmentation for the BRATS challenge. We are currently experimenting with different 3D fully convolutional architectures. We present ...

Mostra'n més