A Short Survey on Deep Learning for Multimodal Integration: Applications, Future Perspectives and Challenges

Deep learning has achieved state-of-the-art performances in several research applications nowadays: from computer vision to bioinformatics, object detection image generation. In the context of such newly developed deep-learning approaches, we can define concept multimodality. The objective this field is implement methodologies which use modalities as input features perform predictions. this, there a strong analogy with respect what happens human cognition, since rely on different senses make decisions. article, present short survey multimodal integration using methods. first instance, comprehensively review multimodality, describing it two-dimensional perspective. First, provide, fact, taxonomical description multimodality concept. Secondly, second dimension one fusion approaches deep learning. Eventually, describe four following fields research: speech recognition, sentiment analysis, forensic and processing.