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SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
9 years 2 months ago
Proximity-Based Anomaly Detection Using Sparse Structure Learning.
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe,...
CVPR
2009
IEEE
10 years 15 days ago
Learning General Optical Flow Subspaces for Egomotion Estimation and Detection of Motion Anomalies
This paper deals with estimation of dense optical flow and ego-motion in a generalized imaging system by exploiting probabilistic linear subspace constraints on the flow. We dea...
Richard Roberts (Georgia Institute of Technology),...
ATAL
2015
Springer
3 years 1 months ago
Adaptation from Sparse Observations through Detection and Correction of Model Anomalies
To make intelligent decisions, robots often use models of the effects of their actions on the world. Unfortunately, it is often infeasible to have the perfect knowledge and compu...
Juan Pablo Mendoza
TGRS
2016
50views more  TGRS 2016»
3 years 1 months ago
Anomaly Detection in Hyperspectral Images Based on Low-Rank and Sparse Representation
Abstract—A novel method for anomaly detection in hyperspectral images (HSIs) is proposed based on low-rank and sparse representation. The proposed method is based on the separati...
Yang Xu, Zebin Wu, Jun Li, Antonio J. Plaza, Zhihu...
ATAL
2015
Springer
3 years 1 months ago
Detecting and Correcting Model Anomalies in Subspaces of Robot Planning Domains
Making decisions based on accurate models enables robots to exploit domain knowledge to act intelligently. However, in many realistic domains, it is impossible to have globally ac...
Juan Pablo Mendoza, Manuela M. Veloso, Reid G. Sim...
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