Zobrazeno 1 - 10
of 742
pro vyhledávání: '"Silva, Sara P."'
Autor:
Verdera, Jordina Aviles, Silva, Sara Neves, Tomi-Tricot, Raphael, Hall, Megan, Story, Lisa, Malik, Shaihan J, Hajnal, Joseph V, Rutherford, Mary A, Hutter, Jana
Purpose: To provide real-time quantitative organ-specific information - specifically placental and brain T2* - to allow optimization of the MR examination to the individual patient. Methods: A FIRE-based real-time setup segmenting placenta and fetal
Externí odkaz:
http://arxiv.org/abs/2409.16878
Autor:
Silva, Sara Neves, Woodgate, Tomas, McElroy, Sarah, Cleri, Michela, Clair, Kamilah St, Verdera, Jordina Aviles, Payette, Kelly, Uus, Alena, Story, Lisa, Lloyd, David, Rutherford, Mary A, Hajnal, Joseph V, Pushparajah, Kuberan, Hutter, Jana
Two subsequent deep learning networks, one localizing the fetal chest and one identifying a set of landmarks on a coronal whole-uterus balanced steady-state free precession scan, were trained on 167 and 71 fetal datasets across field strengths, acqui
Externí odkaz:
http://arxiv.org/abs/2408.06326
Autor:
Silva, Sara Neves, McElroy, Sarah, Verdera, Jordina Aviles, Colford, Kathleen, Clair, Kamilah St, Tomi-Tricot, Raphael, Uus, Alena, Ozenne, Valery, Hall, Megan, Story, Lisa, Pushparajah, Kuberan, Rutherford, Mary A, Hajnal, Joseph V, Hutter, Jana
Purpose: Widening the availability of fetal MRI with fully automatic real-time planning of radiological brain planes on 0.55T MRI. Methods: Deep learning-based detection of key brain landmarks on a whole-uterus EPI scan enables the subsequent fully a
Externí odkaz:
http://arxiv.org/abs/2401.10441
Deep learning models trained with large amounts of data have become a recent and effective approach to predictive problem solving -- these have become known as "foundation models" as they can be used as fundamental tools for other applications. While
Externí odkaz:
http://arxiv.org/abs/2312.12880
A knowledge graph is a powerful representation of real-world entities and their relations. The vast majority of these relations are defined as positive statements, but the importance of negative statements is increasingly recognized, especially under
Externí odkaz:
http://arxiv.org/abs/2308.03447
Publikováno v:
International Conference on Principles of Knowledge Representation and Reasoning 2023
Knowledge graphs represent facts about real-world entities. Most of these facts are defined as positive statements. The negative statements are scarce but highly relevant under the open-world assumption. Furthermore, they have been demonstrated to im
Externí odkaz:
http://arxiv.org/abs/2307.11719
Knowledge graphs represent real-world entities and their relations in a semantically-rich structure supported by ontologies. Exploring this data with machine learning methods often relies on knowledge graph embeddings, which produce latent representa
Externí odkaz:
http://arxiv.org/abs/2306.12687
Autor:
Rodrigues, Nuno M., Batista, João E., Trujillo, Leonardo, Duarte, Bernardo, Giacobini, Mario, Vanneschi, Leonardo, Silva, Sara
We present a novel approach for time series classification where we represent time series data as plot images and feed them to a simple CNN, outperforming several state-of-the-art methods. We propose a simple and highly replicable way of plotting the
Externí odkaz:
http://arxiv.org/abs/2102.04179
Autor:
Batista, João E., Silva, Sara
One problem found when working with satellite images is the radiometric variations across the image and different images. Intending to improve remote sensing models for the classification of burnt areas, we set two objectives. The first is to underst
Externí odkaz:
http://arxiv.org/abs/2002.00053
Fitness landscapes are a useful concept to study the dynamics of meta-heuristics. In the last two decades, they have been applied with success to estimate the optimization power of several types of evolutionary algorithms, including genetic algorithm
Externí odkaz:
http://arxiv.org/abs/2001.11272