Deep Convolutional Network

Deep Convolutional Network

Hidden Cell

Input Cell


Convolution or Pool

Output Cell

Deep Convolutional Network (DBN)

publish time: 2021-05-20
Lisa Anderson

In machine learning, a deep belief network is a generative graphical model, or alternatively a class of deep neural networks, composed of multiple layers of latent variables, known as hidden units, with connections between the layers but not between units within each layer. One can use EdrawMax or EdrawMax Online to create highly customizable deep convolutional network diagrams. Deep-belief networks are used to recognize, cluster, and generate images, video sequences, and motion-capture data. It should be noted here that with the advancement of technology, deep belief networks have mostly fallen out of favor and are rarely used, even compared to other unsupervised or generative learning algorithms.

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