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Keutzer, \u201cSqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5 MB model size,\u201d Feb. 2016, arxiv:1602.07360."},{"key":"ref27","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1162\/tacl_a_00269","article-title":"Densely connected graph convolutional networks for graph-to-sequence learning","volume":"7","author":"Guo","year":"Jun. 2019","journal-title":"Transact. Assoc. Computat. Linguist."},{"key":"ref28","series-title":"2017 Int. Conf. on Eng. and Technol. (ICET)","first-page":"1","article-title":"Understanding of a convolutional neural network","author":"Albawi","year":"2017"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","article-title":"DeepLab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs","volume":"40","author":"Chen","year":"Apr. 2018","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref30","unstructured":"P. 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