Code_Conquerors@DravidianLangTech 2025: Multimodal Misogyny Detection in Dravidian Languages Using Vision Transformer and BERT

AbstractThis research focuses on misogyny detection in Dravidian languages using multimodal techniques. It leverages advanced machine learning models, including Vision Transformers (ViT) for image analysis and BERT-based transformers for text processing. The study highlights the challenges of working with regional datasets and addresses these with innovative preprocessing and model training strategies. The evaluation reveals significant improvements in detection accuracy, showcasing the potential of multimodal approaches in combating online abuse in underrepresented languages.