Empowering AI Research: Approaches and Techniques of Deep Learning for Multimodal Data Analysis : vTools Events

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Empowering AI Research: Approaches and Techniques of Deep Learning for Multimodal Data Analysis

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Objectives of the FDP

To introduce Multimodal AI Fundamentals about the significance of multimodal data (text, image, audio, video) and its role in real-world AI applications.
To Explore Deep Learning & Fusion Techniques to cover architectures and fusion strategies (early, late, hybrid) for integrating diverse data modalities.
To provide practical experience using Python, TensorFlow, PyTorch, and Hugging Face for building multimodal AI models.
To Highlight State-of-the-Art Models & Applications: Discuss leading frameworks like CLIP, VisualBERT, GPT-4o, and showcase case studies in healthcare, surveillance, education, and more.
To discuss challenges, trends & research directions, current challenges (e.g., data heterogeneity, missing modalities), promote interdisciplinary collaboration, and encourage advanced research projects.