Day-33 Computer Vision Learning 𝗙𝗿𝗮𝗰𝘁𝗮𝗹𝗡𝗲𝘁 by Univerisity of Chicago and Toyota Institute of Technology at Chicago has designed. Follow me for similar post : 🇮🇳 Ashish Patel Interesting Facts : 🔸 It is published in 2017 #ICLR , which has already got over 583 citations 🔸 When VGGNet is starting to degrade when it goes from 16 layers (VGG-16) to 19 layers (VGG-19), FractalNet can go up to 40 layers or even 80 layers. ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/eJGBNQS Pytorch : https://bit.ly/3oB8Mnz Keras : https://bit.ly/3pBM6Vo Tensorflow : https://bit.ly/3oF12kn ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸 Fractal, Comes from geometry. The so-called fractal is to solve a problem from multiple levels, multiple angles, and multiple components. 🔸 Fractal Architecture: A Simple Fractal Expansion (Left), Recursively Stacking of Fractal Expansion as One Block (Middle), 5 Blocks Cascaded as FractalNet (Right) More in comments #computervision #data #artificialintelligence
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🔸 Two types of Droppath : 1) Local: A join drops each input with fixed probability, but it is sure that there is at least one survives. 2)Global: A single path is selected for the entire network.
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5yThanks for sharing 🇮🇳 Ashish Patel