Zobrazeno 1 - 10
of 192
pro vyhledávání: '"Falcão, Alexandre X"'
Medical image segmentation is a relevant problem, with deep learning being an exponent. However, the necessity of a high volume of fully annotated images for training massive models can be a problem, especially for applications whose images present a
Externí odkaz:
http://arxiv.org/abs/2406.03225
Brain tumor image segmentation is a challenging research topic in which deep-learning models have presented the best results. However, the traditional way of training those models from many pre-annotated images leaves several unanswered questions. He
Externí odkaz:
http://arxiv.org/abs/2403.12748
Accurate brain tumor segmentation in the early stages of the disease is crucial for the treatment's effectiveness, avoiding exhaustive visual inspection of a qualified specialist on 3D MR brain images of multiple protocols (e.g., T1, T2, T2-FLAIR, T1
Externí odkaz:
http://arxiv.org/abs/2402.05218
Autor:
Malmberg, Filip, Falcão, Alexandre X.
This paper concerns the efficient implementation of a method for optimal binary labeling of graph vertices, originally proposed by Malmberg and Ciesielski (2020). This method finds, in quadratic time with respect to graph size, a labeling that global
Externí odkaz:
http://arxiv.org/abs/2304.12642
Publikováno v:
In Computers & Graphics November 2024 124
Publikováno v:
In Information Sciences February 2025 692
Early detection of COVID-19 is vital to control its spread. Deep learning methods have been presented to detect suggestive signs of COVID-19 from chest CT images. However, due to the novelty of the disease, annotated volumetric data are scarce. Here
Externí odkaz:
http://arxiv.org/abs/2111.08710
Training deep neural networks is challenging when large and annotated datasets are unavailable. Extensive manual annotation of data samples is time-consuming, expensive, and error-prone, notably when it needs to be done by experts. To address this is
Externí odkaz:
http://arxiv.org/abs/2109.02717
Autor:
Afonso, Luis C. S., Pereira, Clayton R., Weber, Silke A. T., Hook, Christian, Falcão, Alexandre X., Papa, João P.
Bag-of-Visual Words (BoVW) and deep learning techniques have been widely used in several domains, which include computer-assisted medical diagnoses. In this work, we are interested in developing tools for the automatic identification of Parkinson's d
Externí odkaz:
http://arxiv.org/abs/2102.09312
A technique named Feature Learning from Image Markers (FLIM) was recently proposed to estimate convolutional filters, with no backpropagation, from strokes drawn by a user on very few images (e.g., 1-3) per class, and demonstrated for coconut-tree im
Externí odkaz:
http://arxiv.org/abs/2012.12108