Multimodal fusionContextual informationAttention modelBidirectional LSTMDue to the availability of an enormous amount of multimodal content on the social web and its applications, automatic sentiment analysis, and emotion detection has become an important and widely researched topic. Improving the quality of...
Multimodal Contextual Interactions of Entities: A Modality Circular Contrastive and Fusion Approach for Link Prediction(MoCi) - MoCiGitHub/MoCi
contextual informationevolutionary computingfeature selectionmultimodal fusionThe availability of the humongous amount of multimodal content on the internet, the multimodal sentiment classification, and emotion detection has become the most researched topic. The feature selection, context extraction, and multi‐...
Inter-modal fusionMulti-level contextual informationBidirectional recurrent neural networkThe recent advancements in the Internet technology and its associated services, led the users to post a large amount of multimodal data into social media Web sites, online shopping portals, video repositories, etc. ...
Correction to: Attention-based multimodal contextual fusion for sentiment and emotion classification using bidirectional LSTMdoi:10.1007/s11042-021-10591-yEMOTIONSCLASSIFICATIONA Correction to this paper has been published: https://doi.org/10.1007/s11042-021-10591-yHuddar, Mahesh ...
Multimodal sentiment analysis, a significant challenge in artificial intelligence, necessitates the integration of various data modalities for accurate human emotion interpretation. This study introduces the Advanced Multimodal Sentiment Analysis with Enhanced Contextual Fusion and Robustness (AMSA-ECFR) framework...