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This project deals with the task "Image Classification for Argumentation" for the Touché 2023 dataset. It attempts to classify argumentative images into a relevant topic using extracted annotation labels from the computer vision APIs Google Cloud Vision and Clarifai. For this purpose, the results of different classification models are compared with each other. Our approach follows the AVCA framework of Araujo et al.

Unüberwachtes Lernen mittels Autoencoder auf Genexpressionsdaten des Human Cell Atlas

This Git contains the files for the different models used in his Bachelor thesis.