Update 2021-11-18-how-to-train-state-of-the-art-models-using-torchvision-latest-primitives.md

Author: pytorchsam

_posts/2021-11-18-how-to-train-state-of-the-art-models-using-torchvision-latest-primitives.md

@@ -1,6 +1,6 @@
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 layout: blog_detail
-title: 'How to train state-of-the-art models using TorchVision’s latest primitives'
+title: 'How to Train State-Of-The-Art Models Using TorchVision’s Latest Primitives'
 author: Vasilis Vryniotis
 featured-img: 'assets/images/fx-image2.png'
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@@ -388,4 +388,4 @@ We would like to thank Piotr Dollar, Mannat Singh and Hugo Touvron for providin
 11. Terrance DeVries, Graham W. Taylor. “Improved Regularization of Convolutional Neural Networks with Cutout”
 12. Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, Zbigniew Wojna. “Rethinking the Inception Architecture for Computer Vision”
 13. Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin, David Lopez-Paz. “mixup: Beyond Empirical Risk Minimization”
-14. Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, Youngjoon Yoo. “CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features”
+14. Sangdoo Yun, Dongyoon Han, Seong Joon Oh, Sanghyuk Chun, Junsuk Choe, Youngjoon Yoo. “CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features”