141 citations · 766 across the 81 of their papers we have counts for
6 papers · 1 filter
Sparse Coding with Fast Image Alignment via Large Displacement Optical Flow
Xiaoxia Sun, Nasser M. Nasrabadi, Trac D. Tran
Sparse representation-based classifiers have shown outstanding accuracy and robustness in image classification tasks even with the presence of intense noise and occlusion. However,…
Semi-supervised Multi-sensor Classification via Consensus-based Multi-View Maximum Entropy Discrimination
Tianpei Xie, Nasser M. Nasrabadi, Alfred O. Hero
In this paper, we consider multi-sensor classification when there is a large number of unlabeled samples. The problem is formulated under the multi-view learning framework and a Co…
Learning to classify with possible sensor failures
Tianpei Xie, Nasser M. Nasrabadi, Alfred O. Hero
In this paper, we propose a general framework to learn a robust large-margin binary classifier when corrupt measurements, called anomalies, caused by sensor failure might be presen…
Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification
Soheil Bahrampour, Nasser M. Nasrabadi, Asok Ray +1
Dictionary learning algorithms have been successfully used in both reconstructive and discriminative tasks, where the input signal is represented by a linear combination of a few d…
Task-Driven Dictionary Learning for Hyperspectral Image Classification with Structured Sparsity Constraints
Xiaoxia Sun, Nasser M. Nasrabadi, Trac D. Tran
Sparse representation models a signal as a linear combination of a small number of dictionary atoms. As a generative model, it requires the dictionary to be highly redundant in ord…
Multimodal Task-Driven Dictionary Learning for Image Classification
Soheil Bahrampour, Nasser M. Nasrabadi, Asok Ray +1
Dictionary learning algorithms have been successfully used for both reconstructive and discriminative tasks, where an input signal is represented with a sparse linear combination o…