deep neural net algorithm dnn Search Results


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SPECTRO Analytical spectro-temporal deep neural network
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Comparison of the proposed <t> CNN </t> model with other works in terms of accuracy of the recognition rate.
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Comparison of the proposed <t> CNN </t> model with other works in terms of accuracy of the recognition rate.
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Comparison of the proposed <t> CNN </t> model with other works in terms of accuracy of the recognition rate.
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Baier labs deep neural network
Comparison of the proposed <t> CNN </t> model with other works in terms of accuracy of the recognition rate.
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Deepmind Technologies Ltd deep neural network dnn
Comparison of the proposed <t> CNN </t> model with other works in terms of accuracy of the recognition rate.
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Lunit Inc deep convolutional neural network
Comparison of the proposed <t> CNN </t> model with other works in terms of accuracy of the recognition rate.
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Comparison of the proposed <t> CNN </t> model with other works in terms of accuracy of the recognition rate.
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Panoptes Pharma GmbH multi-resolution deep convolutional neural network
Comparison of the proposed <t> CNN </t> model with other works in terms of accuracy of the recognition rate.
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EyeTracking Inc deep convolutional neural networks
Comparison of the proposed <t> CNN </t> model with other works in terms of accuracy of the recognition rate.
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BioMimetic Therapeutics deep convolutional neural networks
Comparison of the proposed <t> CNN </t> model with other works in terms of accuracy of the recognition rate.
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Image Search Results


Comparison of the proposed  CNN  model with other works in terms of accuracy of the recognition rate.

Journal: PeerJ Computer Science

Article Title: An efficient multi-factor authentication scheme based CNNs for securing ATMs over cognitive-IoT

doi: 10.7717/peerj-cs.381

Figure Lengend Snippet: Comparison of the proposed CNN model with other works in terms of accuracy of the recognition rate.

Article Snippet: Iris recognition using deep Convolutional Neural Network (CNN) as a feature extractor and fully connected neural network (FCNN), with the Softmax layer as a classifier, is presented.

Techniques: Comparison, Extraction, Isolation