“…It has shown outstanding performance in solving many problems in computer vision and biomedical applications. (Giordano et al, 2005;LeCun, Bengio, & Hinton, 2015;Wang et al, 2016) Lindner et al (Lindner et al, 2016) Arik et al (Arik et al, 2017), conducted deep learning-based 2D cephalometry using CNN, a rapidly developing deep learning algorithm that uses a variation of multilayer perceptrons (LeCun, 2015), inspired by the connectivity of the biological nervous system. (Huang & LeCun, 2006) It is especially suitable for image processing and recognition in that it exploits spatial correlations by imposing local connectivity patterns.…”