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Topology Repairing of Disconnected Pulmonary Airways and Vessels: Baselines and a Dataset

Related publications (44)

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Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Guillermo Ortiz Jimenez, Apostolos Modas

Driven by massive amounts of data and important advances in computational resources, new deep learning systems have achieved outstanding results in a large spectrum of applications. Nevertheless, our current theoretical understanding on the mathematical fo ...

2020

The study of how people schedule their daily activities is of interest in the context of transport demand forecasting using activity based-models, where activity schedules are generated in order to estimate the trip demand they produce. Machine learning ha ...

2020

On Vacuous and Non-Vacuous Generalization Bounds for Deep Neural Networks.

Konstantinos Pitas

Deep neural networks have been empirically successful in a variety of tasks, however their theoretical understanding is still poor. In particular, modern deep neural networks have many more parameters than training data. Thus, in principle they should over ...

EPFL2020

Micrometer-resolution X-ray tomographic full-volume reconstruction of an intact post-mortem juvenile rat lung

Goran Lovric, Marco Stampanoni, Anders Larsson

In this article, we present an X-ray tomographic imaging method that is well suited for pulmonary disease studies in animal models to resolve the full pathway from gas intake to gas exchange. Current state-of-the-art synchrotron-based tomographic phase-con ...

SPRINGER2020

Learning new physics from a machine

Raffaele Tito D'Agnolo, Andrea Wulzer

We propose using neural networks to detect data departures from a given reference model, with no prior bias on the nature of the new physics responsible for the discrepancy. The virtues of neural networks as unbiased function approximants make them particu ...

AMER PHYSICAL SOC2019

Aspergillus fumigatus (A. fumigatus) is a ubiquitous fungus of clinical importance associated with development of various pulmonary diseases and allergic hypersensitivity reactions. It is protected against environmental stress by a cell wall that contains ...

FRONTIERS MEDIA SA2018

Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography

Jan Sickmann Hesthaven

We study the feasibility of data based machine learning applied to ultrasound tomography to estimate water-saturated porous material parameters. In this work, the data to train the neural networks is simulated by solving wave propagation in coupled porovis ...

2018

Learning embeddings: efficient algorithms and applications

Cijo Jose

Learning to embed data into a space where similar points are together and dissimilar points are far apart is a challenging machine learning problem. In this dissertation we study two learning scenarios that arise in the context of learning embeddings and o ...

École Polytechnique Fédérale de Lausanne2018

Apartment Structure Estimation Using Fully Convolutional Networks and Graph Model

Jing Zhang

Apartment searching has been a hot demand all over the world. Understanding the apartment structure will significantly contribute to simplifying the searching process. In this project, the fully convolutional networks are applied to generate semantic segme ...

ASSOC COMPUTING MACHINERY2018

Tomographic in vivo microscopy for the study of lung physiology at the alveolar level

Goran Lovric, Marco Stampanoni

Lungs represent the essential part of the mammalian respiratory system, which is reflected in the fact that lung failure still is one of the leading causes of morbidity and mortality worldwide. Establishing the connection between macroscopic observations o ...

2017