Convolutional Autoencoder for Email Spam Detection


In this paper, I talk about a novel technique for email spam detection. Using the extremely adept pattern recognition abilities of Autoencoders, I designed a Convolutional Autoencoder network to analyze and classify emails as either ham (legitimate) or spam (illegitimate/scam) emails. With promising results, this type of model could help revolutionize email spam detection and tagging, making everyone’s inbox less crowded with emails they don’t want to read

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DigitalCommons@Kennesaw State University

Last time updated on 23/01/2024

This paper was published in DigitalCommons@Kennesaw State University.

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