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Recent Submissions
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MRI brain tumor segmentation and uncertainty estimation using 3D-UNet architectures
(Springer Nature, 2021)
Part of book or chapter of book
Open AccessAutomation of brain tumor segmentation in 3D magnetic resonance images (MRIs) is key to assess the diagnostic and treatment of the disease. In recent years, convolutional neural networks (CNNs) have shown improved results ... -
Enhancing online knowledge graph population with semantic knowledge
(Springer, 2020-11-01)
Part of book or chapter of book
Open AccessKnowledge Graphs (KG) are becoming essential to organize, represent and store the world’s knowledge, but they still rely heavily on humanly-curated structured data. Information Extraction (IE) tasks, like disambiguating ... -
Unsupervised GRN Ensemble
(Springer, 2019)
Part of book or chapter of book
Restricted access - publisher's policyInferring gene regulatory networks from expression data is a very challenging problem that has raised the interest of the scientific community. Different algorithms have been proposed to try to solve this issue, but it has ... -
Cascaded V-Net using ROI masks for brain tumor segmentation
(Springer, 2018)
Part of book or chapter of book
Restricted access - publisher's policyThis book constitutes revised selected papers from the Third International MICCAI Brainlesion Workshop, BrainLes 2017, as well as the International Multimodal Brain Tumor Segmentation, BraTS, and White Matter Hyperintensities, ... -
Hierarchical object detection with deep reinforcement learning
(IOS Press, 2017-11-23)
Part of book or chapter of book
Restricted access - publisher's policyDeep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, ... -
Object retrieval with deep convolutional features
(IOS Press, 2017-11-23)
Part of book or chapter of book
Restricted access - publisher's policyDeep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, ... -
3D convolutional neural networks for brain tumor segmentation: a comparison of multi-resolution architectures
(Springer, 2017-04-24)
Part of book or chapter of book
Open Access -
Time-consistent estimation of end-effectors from RGB-D data
(Springer, 2016-02-04)
Part of book or chapter of book
Open AccessEnd-effectors are usually related to the location of the free end of a kinematic chain. Each of them contains rich structure information about the entity. Hence, estimating stable end-effectors of different ... -
3D point cloud video segmentation based on interaction analysis
(Springer, 2016-11-24)
Part of book or chapter of book
Open AccessGiven the widespread availability of point cloud data from consumer depth sensors, 3D segmentation becomes a promising building block for high level applications such as scene understanding and interaction analysis. It ... -
Neighborhood filters and the recovery of 3D information
(2015-09-01)
Part of book or chapter of book
Restricted access - publisher's policy -
Neighborhood filters and the recovery of 3D information
(2011)
Part of book or chapter of book
Restricted access - publisher's policyFollowing their success in image processing (see Chap. 26), neighborhood filters have been extended to 3D surface processing. This adaptation is not straightforward. It has led to several variants for surfaces depending ... -
Region-based filtering of images and video sequences: a morphological viewpoint
(Academic Press, 2001)
Part of book or chapter of book
Restricted access - publisher's policy
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