2 citations · 2 across the 5 of their papers we have counts for
5 papers
Assessing the Alignment of Popular CNNs to the Brain for Valence Appraisal
Laurent Mertens, Elahe' Yargholi, Laura Van Hove +3
Convolutional Neural Networks (CNNs) are a popular type of computer model that have proven their worth in many computer vision tasks. Moreover, they form an interesting study objec…
Enhancing Computer Vision with Knowledge: a Rummikub Case Study
Simon Vandevelde, Laurent Mertens, Sverre Lauwers +1
Artificial Neural Networks excel at identifying individual components in an image. However, out-of-the-box, they do not manage to correctly integrate and interpret these components…
EmoCAM: Toward Understanding What Drives CNN-based Emotion Recognition
Youssef Doulfoukar, Laurent Mertens, Joost Vennekens
Convolutional Neural Networks are particularly suited for image analysis tasks, such as Image Classification, Object Recognition or Image Segmentation. Like all Artificial Neural N…
FindingEmo: An Image Dataset for Emotion Recognition in the Wild
Laurent Mertens, Elahe' Yargholi, Hans Op de Beeck +2
We introduce FindingEmo, a new image dataset containing annotations for 25k images, specifically tailored to Emotion Recognition. Contrary to existing datasets, it focuses on compl…
Compressing Word Embeddings Using Syllables
Laurent Mertens, Joost Vennekens
This work examines the possibility of using syllable embeddings, instead of the often used -gram embeddings, as subword embeddings. We investigate this for two languages: Englis…