91 citations · 138 across the 9 of their papers we have counts for
9 papers
Measuring economic activity from space: a case study using flying airplanes and COVID-19
Mauricio Pamplona Segundo, Allan Pinto, Rodrigo Minetto +2
This work introduces a novel solution to measure economic activity through remote sensing for a wide range of spatial areas. We hypothesized that disturbances in human behavior cau…
A Soft Computing Approach for Selecting and Combining Spectral Bands
Juan F. H. Albarracín, Rafael S. Oliveira, Marina Hirota +2
We introduce a soft computing approach for automatically selecting and combining indices from remote sensing multispectral images that can be used for classification tasks. The pro…
Parallax Motion Effect Generation Through Instance Segmentation And Depth Estimation
Allan Pinto, Manuel A. Córdova, Luis G. L. Decker +8
Stereo vision is a growing topic in computer vision due to the innumerable opportunities and applications this technology offers for the development of modern solutions, such as vi…
Multimodal Prediction based on Graph Representations
Icaro Cavalcante Dourado, Salvatore Tabbone, Ricardo da Silva Torres
This paper proposes a learning model, based on rank-fusion graphs, for general applicability in multimodal prediction tasks, such as multimodal regression and image classification.…
Fusion vectors: Embedding Graph Fusions for Efficient Unsupervised Rank Aggregation
Icaro Cavalcante Dourado, Ricardo da Silva Torres
The vast increase in amount and complexity of digital content led to a wide interest in ad-hoc retrieval systems in recent years. Complementary, the existence of heterogeneous data…
Unsupervised Graph-based Rank Aggregation for Improved Retrieval
Icaro Cavalcante Dourado, Daniel Carlos Guimarães Pedronette, Ricardo da Silva Torres
This paper presents a robust and comprehensive graph-based rank aggregation approach, used to combine results of isolated ranker models in retrieval tasks. The method follows an un…
Link Prediction in Dynamic Graphs for Recommendation
Samuel G. Fadel, Ricardo da S. Torres
Recent advances in employing neural networks on graph domains helped push the state of the art in link prediction tasks, particularly in recommendation services. However, the use o…
Exploiting ConvNet Diversity for Flooding Identification
Keiller Nogueira, Samuel G. Fadel, Ícaro C. Dourado +7
Flooding is the world's most costly type of natural disaster in terms of both economic losses and human causalities. A first and essential procedure towards flood monitoring is bas…
Approximate Similarity Search for Online Multimedia Services on Distributed CPU-GPU Platforms
George Teodoro, Eduardo Valle, Nathan Mariano +3
Similarity search in high-dimentional spaces is a pivotal operation found a variety of database applications. Recently, there has been an increase interest in similarity search for…