1 citations · 1 across the 4 of their papers we have counts for
5 papers
Greenery Segmentation In Urban Images By Deep Learning
Artur A. M. Oliveira, Nina S. T. Hirata, Roberto Hirata
Vegetation is a relevant feature in the urban scenery and its awareness can be measured in an image by the Green View Index (GVI). Previous approaches to estimate the GVI were base…
Kernels on fuzzy sets: an overview
Jorge Guevara, Roberto Hirata, Stéphane Canu
This paper introduces the concept of kernels on fuzzy sets as a similarity measure for -valued functions, a.k.a. \emph{membership functions of fuzzy sets}. We defined the fo…
A logical-based corpus for cross-lingual evaluation
Felipe Salvatore, Marcelo Finger, Roberto Hirata
At present, different deep learning models are presenting high accuracy on popular inference datasets such as SNLI, MNLI, and SciTail. However, there are different indicators that…
Concave losses for robust dictionary learning
Rafael Will M de Araujo, Roberto Hirata, Alain Rakotomamonjy
Traditional dictionary learning methods are based on quadratic convex loss function and thus are sensitive to outliers. In this paper, we propose a generic framework for robust dic…
maigesPack: A Computational Environment for Microarray Data Analysis
Gustavo H. Esteves, Roberto Hirata
Microarray technology is still an important way to assess gene expression in molecular biology, mainly because it measures expression profiles for thousands of genes simultaneously…