The Architecture of Convnets and Data Processing. Advantages of Convolutional Neural Networks


Essay, 2020

26 Pages, Grade: 1,3

Anonymous


Excerpt


Content

1 Introduction
1.1 Motivation

2 The Architecture of ConvNets and Data Processing
2.1 The Convolutional Layer
2.1.1 Hyperparameters and filter weights
2.1.2 Activation functions und Biases
2.2 The Pooling Layer
2.3 The Fully-Connected Layer
2.4 Processing of colored images

3 Advantages of Convolutional Neural Networks
3.1 Parameter Reduction
3.1.1 Weight Sharing in Convolutional Layers
3.1.2 Dimensionality Reduction via Pooling
3.2 Object Detection

4 Application to the MNIST Dataset

5 Summary

6 Literature

7 Appendix
7.1 Python Code

Excerpt out of 26 pages

Details

Title
The Architecture of Convnets and Data Processing. Advantages of Convolutional Neural Networks
College
University of Ulm
Grade
1,3
Year
2020
Pages
26
Catalog Number
V914160
ISBN (eBook)
9783346213075
ISBN (Book)
9783346213082
Language
English
Notes
Das Convolutional Neural Network ist eine besondere Form des künstlichen neuronalen Netzwerks. Es besitzt mehrere Faltungsschichten und ist für maschinelles Lernen und Anwendungen mit Künstlicher Intelligenz (KI) im Bereich Bild- und Spracherkennung sehr gut geeignet.
Keywords
advantages, architecture, convnets, convolutional, data, networks, neural, processing
Quote paper
Anonymous, 2020, The Architecture of Convnets and Data Processing. Advantages of Convolutional Neural Networks, Munich, GRIN Verlag, https://www.grin.com/document/914160

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