Multimodality and Data Fusion Techniques in Deep Learning

Explore the concept of multimodal deep learning and data fusion techniques in this 23-minute conference talk from the ISTA Conference. Delve into the principle of multimodality and its alignment with human cognition. Examine real-world examples of multimodal networks that combine various data types such as audio, video, accelerometer, and text. Learn about early, late, and hybrid fusion techniques, their applications, advantages, and potential limitations. Gain insights into the future of multimodal deep learning, including potential developments and challenges. Presented by Petar Velev, Senior Software Engineer at Bosch Engineering Center Sofia, this talk offers a concise yet comprehensive understanding of multimodal deep learning and its transformative potential in the field of AI.

Multimodality and Data Fusion Techniques in Deep Learning