Road Ahead for Multi‐modal Intelligent Sensing in the Deep Learning Era
Ahmed Zoha, Naeem Ramzan, Muhammad Ali Jamshed, Masood Ur Rehman · 2024
In the field of computing and artificial intelligence (AI), multi-modality enables systems to process and integrate information from different sources, such as text, images, video, and audio. This capability enhances perception, allowing machines to understand their environment better and make improved decisions. This chapter explores the opportunities that existing systems present, such as improved accuracy and enhanced insights, as well as the challenges they face. While promising for advancing various fields, multi-modal data fusion faces significant challenges in the age of big data and deep learning. Interpretability remains a crucial concern, prompting the exploration of hybrid approaches that combine statistical signal processing with deep learning, as well as incorporating human expertise for decision-making. Additionally, ethical considerations surrounding privacy, bias, and transparency must be carefully addressed through clear governance policies, bias mitigation techniques, and explainable AI methods.