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Deep convolutional neural network

Deep convolutional neural network D6e0j
AleXNet is a deep convolutional neural network that was trained on a large dataset(Image Net) to classify the 1. 2 million high-resolution images with 1000 different classes(Alex Krizhevsky and et al, 2017), in the current study, our data sets were employed on Alexnet by using transfer learning where consider transfer learning is an efficient and powerful solution for many classification problems. Training requires enough data and computer time, but much less than training from scratch (see Figure 2 for a comparison with pre-trained networks and training from scratch) (Bengio, 2012), and the result is a network specifically tailored to our objectives. It is beneficial that we use the pre-trained AlexNet architecture to build the network † where Figure 4 shows the AlexNet architecture.
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AleXNet
is a deep convolutional neural
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network
that
was trained
on a large dataset(Image Net) to classify the 1. 2 million high-resolution images with 1000
This phrase/word is too simple and can be replaced with:
different
classes(Alex
Possible spelling mistake found.
Krizhevsky
and
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et al
, 2017), in the
This phrase/word (depending on the context) can be potentially replaced with :
current
study, our data sets
were employed
on
Possible spelling mistake found.
Alexnet
by using transfer learning where consider transfer learning is an efficient and powerful solution for
This phrase/word is too simple and can be replaced with:
many
classification problems. Training requires
This phrase/word is too simple and can be replaced with:
enough
data and computer time,
This phrase/word is too simple and can be replaced with:
but
much less than training from scratch (
This phrase/word (depending on the context) can be potentially replaced with :
see
Figure 2 for a comparison with pre-trained
You use this word too often, consider replacing it with
networks
and training from scratch) (
Possible spelling mistake found.
Bengio
, 2012), and the result is a
You use this word too often, consider replacing it with
network
specifically
tailored to our objectives. It is beneficial that we
This phrase/word (depending on the context) can be potentially replaced with :
use
the pre-trained
Possible spelling mistake found.
AlexNet
architecture to build the
You use this word too often, consider replacing it with
network
† where Figure 4
This phrase/word (depending on the context) can be potentially replaced with :
shows
the
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AlexNet
architecture.

IELTS essay Deep convolutional neural network

Essay
  American English
1 paragraphs
123 words
This writing has been penalized,
text can't be
less than 250 words in Task 2
and less than 150 words in Task 1
4.0
Overall Band Score
Coherence and Cohesion: 5.5
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  • Use cohesive linking words accurately and appropriately
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Lexical Resource: 5.5
  • Try to vary your vocabulary using accurate synonyms
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  • Check your work for spelling and word formation mistakes
Grammatical Range: 6.5
  • Use a variety of complex and simple sentences
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Task Achievement: 5.0
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    Present relevant ideas
  • Fully explain these ideas
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