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Andrews Cordolino Sobral

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ENGENHARIA DE COMPUTAÇÃO E INTELIGÊNCIA ARTIFICIAL
Robust Low-rank and Sparse Decomposition for Moving Object Detection
Machine Learning for Dummies (without mathematics)
PhD Thesis Defense Presentation: Robust Low-rank and Sparse Decomposition for Moving Object Detection - From Matrices to Tensors
Incremental and Multi-feature Tensor Subspace Learning applied for Background Modeling and Subtraction
Comparison of Matrix Completion Algorithms for Background Initialization in Videos
Double-constrained RPCA based on Saliency Maps for Foreground Detection in Automated Maritime Surveillance
Recent advances on low-rank and sparse decomposition for moving object detection
Online Stochastic Tensor Decomposition for Background Subtraction in Multispectral Video Sequences
Matrix and Tensor Tools for Computer Vision
SPPRA'2013 Paper Presentation
Classificação Automática do Estado do Trânsito Utilizando Propriedades Holísticas