most citedSemi-Automatic Data Annotation guided by Feature Space Projection

40 citations · 41 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Semi-supervised deep learning based on label propagation in a 2D embedded space

Barbara Caroline Benato, Jancarlo Ferreira Gomes, Alexandru Cristian Telea +1

While convolutional neural networks need large labeled sets for training images, expert human supervision of such datasets can be very laborious. Proposed solutions propagate label…

cs.LG202040 cited

Semi-Automatic Data Annotation guided by Feature Space Projection

Barbara Caroline Benato, Jancarlo Ferreira Gomes, Alexandru Cristian Telea +1

Data annotation using visual inspection (supervision) of each training sample can be laborious. Interactive solutions alleviate this by helping experts propagate labels from a few…

cs.LG20201 cited

Supporting Optimal Phase Space Reconstructions Using Neural Network Architecture for Time Series Modeling

Lucas Pagliosa, Alexandru Telea, Rodrigo Mello

The reconstruction of phase spaces is an essential step to analyze time series according to Dynamical System concepts. A regression performed on such spaces unveils the relationshi…

cs.CG2019

Quantitative Comparison of Time-Dependent Treemaps

Eduardo Vernier, Max Sondag, Joao Comba +3

Rectangular treemaps are often the method of choice to visualize large hierarchical datasets. Nowadays such datasets are available over time, hence there is a need for (a) treemaps…

cs.LG2019

Deep Learning Multidimensional Projections

Mateus Espadoto, Nina S. T. Hirata, Alexandru C. Telea

Dimensionality reduction methods, also known as projections, are frequently used for exploring multidimensional data in machine learning, data science, and information visualizatio…