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Deep Residual networks ResNet

Deep Residual networks ResNet RykXM
Deep Residual networks, shortly named as ResNet is developed based on the core idea addressed as shortcut connections or skip connections. These connections provide an alternate pathway for data and gradients to flow, thus making the training possible. The simplest model is ResNet-18 which has 18 layers. The input image size of this model is 224×224×3. It was developed by Kaiming et al. , [20] and was the winner of ILSVRC-2015. The detailed architecture of ResNet- 18 and how to skip connections run in parallel is shown in Fig. 5
Deep Residual networks, shortly named as
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ResNet
is developed
based on the core
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idea
addressed as shortcut
You use this word too often, consider replacing it with
connections
or skip
You use this word too often, consider replacing it with
connections
. These
You use this word too often, consider replacing it with
connections
provide an alternate pathway for data and gradients to flow,
thus
making the training possible. The simplest model is ResNet-18 which has 18 layers. The input image size of this model is 224×224×3. It
was developed
by
Possible spelling mistake found.
Kaiming
et al.
Put a space after the comma, but not before the comma
,
[20] and was the winner of ILSVRC-2015. The detailed architecture of
Possible spelling mistake found.
ResNet
- 18 and how to skip
You use this word too often, consider replacing it with
connections
run in parallel
is shown
in Fig. 5

IELTS essay Deep Residual networks ResNet

Essay
  American English
1 paragraphs
89 words
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4.0
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