<h5>High Level Description</h5><p>This master's thesis aims to develop a robust multimodal fake news detection system capable of effectively identifying misinformation across different social media platforms. The research will focus on novel deep learning architectures for multimodal fusion and explore techniques for effective knowledge transfer between platforms, addressing the evolving challenge of online misinformation.</p><h5>Project Description</h5><p>The project will involve creating a deep learning model that can process and analyze multiple inputs such as text and images from social media platforms.</p><p>The research will focus on developing novel architectures for multimodal fusion and exploring techniques for effective knowledge transfer between platforms. Including data collection, preprocessing pipelines. Compare studies on pre-existing work and implementations to gather knowledge of the domain.</p><h5>Who are we looking for?</h5><p>Bachelor/Master of Science in Computer Science/Engineering</p><h5>Purpose</h5><p>The purpose of this research is to advance the field of fake news detection by developing more effective techniques for multimodal analysis. This could potentially improve the robustness and adaptability of fake news detection systems across different social media environments.</p> •
Last updated on Nov 1, 2024