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Dictionary-based super-resolution is actively studied with successful achievements. However, previous dictionary-based super-resolution methods exploit optimization or nearest neighbor search which has high complexity. In this paper, we propose a low-complexity super-resolution method called the discrete feature transform which performs feature extraction and nearest neighbor search at once. As a...
This paper describes a pedestrian detection method using feature selection based on logistic regression analysis. As the parent features, Haar-like and Histograms of Oriented Gradients (HOG) features are used manually. For the statistical analysis, stepwise forward selection, backward elimination, and Least Absolute Shrinkage and Selection Operator (LASSO) methods are applied to our Logistic Regression...
Feature selection has received attention recently in the field of object detection. A vehicle detection method using feature selection is presented in this work. An efficient feature subset is selected using feature selection methods and each feature subset is evaluated by computing the average error rate in different classification methods. The feature selection methods used in this work are the...
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