EE-559 Deep Learning - Student Poster Session - Deep Learning for Safer Online Spaces

Event details
Date | 29.05.2024 |
Hour | 08:30 › 12:00 |
Location |
ELA 194.1 hall
|
Category | Miscellaneous |
Event Language | English |
Students will be presenting their group projects exploring how deep learning can be harnessed to support a more secure and positive online environment.
Some light refreshments will be served. We welcome you to drop by at your convenience and explore their works. We look forward to seeing you there!
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Background information: project brief
Theme: Deep learning to foster safer online spaces
Scope: The group mini-project aims to support a safer online environment by tackling hate speech in various forms, ranging from text and images to memes, videos, and audio content.
Objective: To develop deep learning models that help foster healthier online interactions by automatically identifying hate speech across diverse content formats. These deep learning models shall be carefully designed to prioritize accuracy and context comprehension, ensuring they differentiate between harmful hate speech and legitimate critical discourse or satire.
Context: Developing deep learning models that help prevent the surfacing of hateful rhetoric will lead to a more respectful online environment where diverse voices can coexist and thrive.
Practical information
- General public
- Free
Contact
- Andrea Cavallaro