Vehicle Recognition Using Rule Based Methods

By J. Siebert. 1987

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Machine Learning, Neural and Statistical Classification (2009, background): “(1984) describe CART, which is a partitioning algorithm developed by statisticians, and Silverman (1986) discusses density estimation methods. For neural net approaches, the book by Hertz et al. (1991) is probably the most comprehensive and reliable. Two excellent texts on pattern recognition are th”
Fast Bayesian hyperparameter optimization on large datasets (2017, methodology): “…we optimized the same SVM hyperparameters (see Table 1) without a surrogate on MNIST and two other prominent UCI datasets (gathered from OpenML (Vanschoren et al., 2014)), vehicle registration (Siebert, 1987) and forest cover types (Blackard and Dean, 1999) with more than 50000 data points.”
ADASYN: Adaptive synthetic sampling approach for imbalanced learning (2008, methodology): “This data set is used to classify a given silhouette as one of four types of vehicles [30].”