activity
20122021
most citedUnsupervised Graph-based Rank Aggregation for Improved Retrieval

22 citations · 37 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CV2021

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…

cs.NE20205 cited

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…

cs.CV20207 cited

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…

cs.CV2019

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.…

cs.CV20193 cited

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…

cs.IR201922 cited

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…