Deconvolutional Network
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Deconvolutional Network

Input Cell

Kernel

Convolution or Pool

Output Cell

Deconvolutional Network (DN)

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publish time: 2021-05-20
Lisa Anderson

Deconvolutional networks are convolutional neural networks (CNN) that work in a reversed process. As the abstract deconvolutional networks suggest, it is also known as deconvolutional neural networks, which are pretty similar in nature to CNN’s run in reverse but are specific applications of artificial intelligence. As the image suggests, deconvolutional networks strive to find lost features or signals that may have previously not been deemed important to a convolutional neural network’s task. The deconvolution of signals can be used in both analysis and synthesis. Instead of creating a Deconvolutional networks diagram from scratch, use EdrawMax or EdrawMax Online to create high-functioning neural network diagrams for biological or other projects.

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