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Hi and welcome to chapter fourteen point three where we talk about resonate 50 arrests 50 was the winner
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of the Eilis our AVC competition in 2015.
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It was developed by district researchers here and present resin that stands for residual network.
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And that's because it uses the concept of residual linning which helps it in a number of ways.
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And I'll talk about those ways now.
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So the beauty of Reznor was that it got around a problem of just making instead of making networks deeper
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and deeper which was the trend back in 2015.
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And by doing that by making it deeper and deeper People were coming up with coming across accuracy becoming
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saturated and integrating rapidly during training which was not good.
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So what resonated was that it introduced a shallow architecture with a deep deep residual learning framework
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and resonate instead of leaving high mid and low mid and high level features.
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It lends residuals by using short cut connections directly connecting the input of the player to an
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end.
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Plus ex-slave.
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So this results in far easier training and resolves to degrading accuracy problem.
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This is what the resonant residual module looks like here.
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Can Take a look.
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Basically this is a x one layer.
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Here goes through this all these layers here and added back to the experts.
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One layer here.
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So now let's move on to Inception vision tree.
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