43 citations · 55 across the 5 of their papers we have counts for
6 papers · 1 filter
Understanding attention-based encoder-decoder networks: a case study with chess scoresheet recognition
Sergio Y. Hayashi, Nina S. T. Hirata
Deep neural networks are largely used for complex prediction tasks. There is plenty of empirical evidence of their successful end-to-end training for a diversity of tasks. Success…
Self-supervised Learning for Astronomical Image Classification
Ana Martinazzo, Mateus Espadoto, Nina S. T. Hirata
In Astronomy, a huge amount of image data is generated daily by photometric surveys, which scan the sky to collect data from stars, galaxies and other celestial objects. In this pa…
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…
Symbol detection in online handwritten graphics using Faster R-CNN
Frank D. Julca-Aguilar, Nina S. T. Hirata
Symbol detection techniques in online handwritten graphics (e.g. diagrams and mathematical expressions) consist of methods specifically designed for a single graphic type. In this…
Image operator learning coupled with CNN classification and its application to staff line removal
Frank D. Julca-Aguilar, Nina S. T. Hirata
Many image transformations can be modeled by image operators that are characterized by pixel-wise local functions defined on a finite support window. In image operator learning, th…
A General Framework for the Recognition of Online Handwritten Graphics
Frank Julca-Aguilar, Harold Mouchère, Christian Viard-Gaudin +1
We propose a new framework for the recognition of online handwritten graphics. Three main features of the framework are its ability to treat symbol and structural level information…