Search Results for author: Verónica Vilaplana

Found 8 papers, 2 papers with code

RGI : Regularized Graph Infomax for self-supervised learning on graphs

no code implementations15 Mar 2023 Oscar Pina, Verónica Vilaplana

Self-supervised learning is gaining considerable attention as a solution to avoid the requirement of extensive annotations in representation learning on graphs.

Graph Neural Network Representation Learning +1

Cascaded V-Net using ROI masks for brain tumor segmentation

no code implementations30 Dec 2018 Adrià Casamitjana, Marcel Catà, Irina Sánchez, Marc Combalia, Verónica Vilaplana

In this work we approach the brain tumor segmentation problem with a cascade of two CNNs inspired in the V-Net architecture \cite{VNet}, reformulating residual connections and making use of ROI masks to constrain the networks to train only on relevant voxels.

Brain Tumor Segmentation Segmentation +1

Saliency maps on image hierarchies

no code implementations19 Aug 2015 Verónica Vilaplana

In this paper we propose two saliency models for salient object segmentation based on a hierarchical image segmentation, a tree-like structure that represents regions at different scales from the details to the whole image (e. g. gPb-UCM, BPT).

Image Segmentation Segmentation +1

Improving Spatial Codification in Semantic Segmentation

no code implementations27 May 2015 Carles Ventura, Xavier Giró-i-Nieto, Verónica Vilaplana, Kevin McGuinness, Ferran Marqués, Noel E. O'Connor

This paper explores novel approaches for improving the spatial codification for the pooling of local descriptors to solve the semantic segmentation problem.

Object Segmentation +1

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