Hate speech and offensive content are increasingly prevalent in online environments, posing significant challenges to social media platforms and their users. Among the various forms of online hate, hate meme images or videos that combine visuals with offensive or hateful text are particularly insidious due to their multimodal nature, making them difficult to detect and moderate. This project’s idea is the development of an advanced system for hate meme detection, employing a combination of Natural Language Processing (NLP) and Computer Vision techniques. The proposed system aims to accurately identify hate memes by analyzing both the textual and visual components of content, leveraging deep learning models like Convolutional Neural Networks (CNNs) for image analysis and Transformer-based models for text processing.