In this paper, we propose a LSTM-based model that enables utterances to capture contextual information from their surroundings in the same video, thus aiding the classification process in multimodal ...

Abstract: In recent years, deep learning technology has developed rapidly, and the field of Natural Language Processing (NLP ... fusion model algorithm. In this study, the performance and ...

ranging from computer vision and speech recognition to NLP. Applying deep learning to sentiment analysis has also become very popular recently. In this paper, we propose a comparative study for ...

"Deep learning allows us to model ... NLP systems to perform complex tasks with such precision, making it invaluable for search and ranking." Rama Krishna also notes the potential for multimodal ...

To cope with these demanding situations, we advise a multi-modal deep ... (NLP), Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM) networks to become aware of and mitigate online ...

creating a model specifically calibrated for this ethnic group. Advanced deep learning methods hold the potential to extract meaningful information from multimodal brain data. The collected research ...