MA-FR-DCNet: an attention-enabled faster regional-based deep convolutional network for multimodal sentiment analysis

Key Points

• This research aims to improve the accuracy of sentiment analysis by using a specialized deep convolutional network framework.
• Developed an attention-enabled faster regional-based deep convolutional network architecture.
• Applied multimodal inputs for comprehensive sentiment analysis.
• Conducted evaluations using various sentiment datasets.
• Achieved an accuracy improvement of 15% compared to traditional models.
• Demonstrated faster processing times with reduced computational costs.
• Showed robust performance across different sentiment analysis tasks.