  This paper describes our contribution to SemEval 2020 Task 8: Memotion
Analysis. Our system learns multi-modal embeddings from text and images in
order to classify Internet memes by sentiment. Our model learns text embeddings
using BERT and extracts features from images with DenseNet, subsequently
combining both features through concatenation. We also compare our results with
those produced by DenseNet, ResNet, BERT, and BERT-ResNet. Our results show
that image classification models have the potential to help classifying memes,
with DenseNet outperforming ResNet. Adding text features is however not always
helpful for Memotion Analysis.
