Day-53 Computer Vision Learning CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features (Image Classification) by NAVER Corp., LINE Plus Corp., and Yonsei University Follow me for similar post : 🇮🇳 Ashish Patel Interesting Facts : 🔸 It is published in 2019 #ICCV, which has already got over 311 citations. 🔸 Outperforms DropBlock, ShakeDrop, Cutout and mixup ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/eU3vvB7 official Code : https://bit.ly/3pFLFsf tensorflow : https://bit.ly/3kcV9Kx pytorch: https://bit.ly/2ZFiifa ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸 Patches are cut and pasted among training images where the ground truth labels are also mixed proportionally to the area of the patches. 🔸 By making efficient use of training pixels and retaining the regularization effect of regional dropout, CutMix consistently outperforms the state-of-the-art augmentation strategies. #computervision #artificialintelligence #innovation
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