2013
DOI: 10.1016/s1874-1029(13)60052-x
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Advance and Prospects of AdaBoost Algorithm

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Cited by 259 publications
(66 citation statements)
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“…It should be noted that reports on the crystal structure of the plate-like grain boundary phase in Allvac 718Plus are not fully resonant. The phase is attributed to being the orthorhombic δ-phase [14,15] (typical for Alloy 718) as well as an hexagonal structure [16,17]. Nevertheless, the heat treatment was performed as follows, with water quenching (WQ) and furnace cooling (FC) between steps: 1040 °C /1h (WQ) + 788 °C/8h (FC) + 704 °C /8h (FC).…”
Section: Experimental Materialsmentioning
confidence: 99%
“…It should be noted that reports on the crystal structure of the plate-like grain boundary phase in Allvac 718Plus are not fully resonant. The phase is attributed to being the orthorhombic δ-phase [14,15] (typical for Alloy 718) as well as an hexagonal structure [16,17]. Nevertheless, the heat treatment was performed as follows, with water quenching (WQ) and furnace cooling (FC) between steps: 1040 °C /1h (WQ) + 788 °C/8h (FC) + 704 °C /8h (FC).…”
Section: Experimental Materialsmentioning
confidence: 99%
“…The basic AdaBoost algorithm can only handle binary classification problems. On this basis, Schapire (1990) proposed a series of derivative algorithms in which the AdaBoost.M1 algorithm can handle multiple classification problems (Cao et al, 2013). The process for the AdaBoost.…”
Section: Adaboost Series Classifiersmentioning
confidence: 99%
“…The integral map can use the same time (constant time) to calculate different features at various scales, thus greatly improving the detection speed. Then the classifiers are trained by the Adaboost algorithm [Cao, Miao, Liu et al (2013)]. each Haar feature weak classifier is trained with the same training set to extract facial features in the image.…”
Section: Face Recognition and Positioningmentioning
confidence: 99%