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A basic autoencoder model using CNNs to analyse online social media videos about immersive museum exhibits.

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CNN-based Autoencoder

The aim of this project is to automatically determine if a given TikTok video is about an immersive museum experience (e.g. Frameless) or a traditional non-immersive one (e.g. Natural History Museum). This should eliminate the need to manually inspect a dataset of videos to tag them all and remove any false positives.

This will be done using an autoencoder (a type of artificial neural network) to identify any defining features that could distinguish both types of video from each other.

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A basic autoencoder model using CNNs to analyse online social media videos about immersive museum exhibits.

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