@conference {12471,
	title = {Automatic target recognition based on simultaneous sparse representation},
	booktitle = {Image Processing (ICIP), 2010 17th IEEE International Conference on},
	year = {2010},
	month = {2010/09//},
	pages = {1377 - 1380},
	abstract = {In this paper, an automatic target recognition algorithm is presented based on a framework for learning dictionaries for simultaneous sparse signal representation and feature extraction. The dictionary learning algorithm is based on class supervised simultaneous orthogonal matching pursuit while a matching pursuit-based similarity measure is used for classification. We show how the proposed framework can be helpful for efficient utilization of data, with the possibility of developing real-time, robust target classification. We verify the efficacy of the proposed algorithm using confusion matrices on the well known Comanche forward-looking infrared data set consisting of ten different military targets at different orientations.},
	keywords = {(artificial, algorithm;feature, based, classification;iterative, classification;learning, Comanche, data, dictionary;matching, extraction;image, forward-looking, infrared, intelligence);military, learning, MATCHING, matrix;dictionary, measure;military, methods;learning, orthogonal, pursuit, pursuit;confusion, recognition;class, recognition;target, representation;feature, representation;sparse, set;automatic, signal, similarity, simultaneous, sparse, supervised, systems;object, target, target;simultaneous, tracking;},
	doi = {10.1109/ICIP.2010.5652306},
	author = {Patel, Vishal M. and Nasrabadi,N.M. and Chellapa, Rama}
}
