7 citations · 7 across the 1 of their papers we have counts for
5 papers
A comprehensive review and new taxonomy on superpixel segmentation
I. B. Barcelos, F. de C. Belém, L. de M. João +3
Superpixel segmentation consists of partitioning images into regions composed of similar and connected pixels. Its methods have been widely used in many computer vision application…
Building Brain Tumor Segmentation Networks with User-Assisted Filter Estimation and Selection
Matheus A. Cerqueira, Flávia Sprenger, Bernardo C. A. Teixeira +1
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…
Self-calibrated convolution towards glioma segmentation
Felipe C. R. Salvagnini, Gerson O. Barbosa, Alexandre X. Falcao +1
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 o…
A Practical Algorithm for Max-Norm Optimal Binary Labeling of Graphs
Filip Malmberg, Alexandre X. Falcão
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…
Linking data separation, visual separation, and classifier performance using pseudo-labeling by contrastive learning
Bárbara Caroline Benato, Alexandre Xavier Falcão, Alexandru-Cristian Telea
Lacking supervised data is an issue while training deep neural networks (DNNs), mainly when considering medical and biological data where supervision is expensive. Recently, Embedd…