Zobrazeno 1 - 10
of 10 036
pro vyhledávání: '"Campello A"'
Autor:
Bai, Jieyun, Zhou, Zihao, Ou, Zhanhong, Koehler, Gregor, Stock, Raphael, Maier-Hein, Klaus, Elbatel, Marawan, Martí, Robert, Li, Xiaomeng, Qiu, Yaoyang, Gou, Panjie, Chen, Gongping, Zhao, Lei, Zhang, Jianxun, Dai, Yu, Wang, Fangyijie, Silvestre, Guénolé, Curran, Kathleen, Sun, Hongkun, Xu, Jing, Cai, Pengzhou, Jiang, Lu, Lan, Libin, Ni, Dong, Zhong, Mei, Chen, Gaowen, Campello, Víctor M., Lu, Yaosheng, Lekadir, Karim
Segmentation of the fetal and maternal structures, particularly intrapartum ultrasound imaging as advocated by the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) for monitoring labor progression, is a crucial first step for
Externí odkaz:
http://arxiv.org/abs/2409.10980
Autor:
Jiang, Jianmei, Wang, Huijin, Bai, Jieyun, Long, Shun, Chen, Shuangping, Campello, Victor M., Lekadir, Karim
The segmentation of the pubic symphysis and fetal head (PSFH) constitutes a pivotal step in monitoring labor progression and identifying potential delivery complications. Despite the advances in deep learning, the lack of annotated medical images hin
Externí odkaz:
http://arxiv.org/abs/2409.06928
Autor:
Fabila, Jorge, Campello, Víctor M., Martín-Isla, Carlos, Obungoloch, Johnes, Leo, Kinyera, Ronald, Amodoi, Lekadir, Karim
Africa faces significant challenges in healthcare delivery due to limited infrastructure and access to advanced medical technologies. This study explores the use of federated learning to overcome these barriers, focusing on perinatal health. We train
Externí odkaz:
http://arxiv.org/abs/2408.17216
Autor:
Röchner, Philipp, Marques, Henrique O., Campello, Ricardo J. G. B., Zimek, Arthur, Rothlauf, Franz
Outlier detection algorithms typically assign an outlier score to each observation in a dataset, indicating the degree to which an observation is an outlier. However, these scores are often not comparable across algorithms and can be difficult for hu
Externí odkaz:
http://arxiv.org/abs/2408.15874
Autor:
Miró-Nicolau, Miquel, Moyà-Alcover, Gabriel, Jaume-i-Capó, Antoni, González-Hidalgo, Manuel, Campello, Maria Gemma Sempere, Sancho, Juan Antonio Palmer
The increasing reliance on Deep Learning models, combined with their inherent lack of transparency, has spurred the development of a novel field of study known as eXplainable AI (XAI) methods. These methods seek to enhance the trust of end-users in a
Externí odkaz:
http://arxiv.org/abs/2405.05766
Autor:
Yerbury, Luke W., Campello, Ricardo J. G. B., Livingston Jr, G. C., Goldsworthy, Mark, O'Neil, Lachlan
Relative Validity Indices (RVIs) such as the Silhouette Width Criterion, Calinski-Harabasz and Davie's Bouldin indices are the most popular tools for evaluating and optimising applications of clustering. Their ability to rank collections of candidate
Externí odkaz:
http://arxiv.org/abs/2404.10351
Autor:
Campello, Betania Silva C, Pelegrina, Guilherme Dean, Pelissari, Renata, Suyama, Ricardo, Duarte, Leonardo Tomazeli
Countries worldwide have been implementing different actions national strategies for Artificial Intelligence (AI) to shape policy priorities and guide their development concerning AI. Several AI indices have emerged to assess countries' progress in A
Externí odkaz:
http://arxiv.org/abs/2402.10122
Autor:
Huang, Hanxun, Campello, Ricardo J. G. B., Erfani, Sarah Monazam, Ma, Xingjun, Houle, Michael E., Bailey, James
Representations learned via self-supervised learning (SSL) can be susceptible to dimensional collapse, where the learned representation subspace is of extremely low dimensionality and thus fails to represent the full data distribution and modalities.
Externí odkaz:
http://arxiv.org/abs/2401.10474
Autor:
Anderberg, Alastair, Bailey, James, Campello, Ricardo J. G. B., Houle, Michael E., Marques, Henrique O., Radovanović, Miloš, Zimek, Arthur
We present a nonparametric method for outlier detection that takes full account of local variations in intrinsic dimensionality within the dataset. Using the theory of Local Intrinsic Dimensionality (LID), our 'dimensionality-aware' outlier detection
Externí odkaz:
http://arxiv.org/abs/2401.05453
Autor:
Karen Brisson-Suárez, José F. Siqueira, Flávio R. F. Alves, Andrea F. Campello, Renata C. V. Rodrigues, Danielle D. Voigt, Kaline Romeiro, Simone C. Loyola-Fonseca, Fabiano L. Heggendorn, Ibrahimu Mdala, Isabela N. Rôças
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract This ex vivo study devised an analytical ex vivo method for infection/disinfection of simulated lateral canals located in the middle and apical segments of the root. The antibacterial effects of supplementary approaches were tested in this m
Externí odkaz:
https://doaj.org/article/1b273182580844e3a5634abdd559d19f
