AIMAI Lab won the best presentation award at RIVF 2021

Date: Dec 31,2021

A research team from Aimesoft Multimodal Artificial Intelligence Lab (AIMAI Lab) won the best presentation award at the 15th IEEE RIVF International Conference on Computing and Communication Technologies (RIVF 2021). 

RIVF (Research, Innovation and Vision for the Future) has become a major scientific event for researchers in the fields of Computing and Communication Technologies in the world since 2003. The conference series has been held alternatively between the northern and southern parts of Vietnam. The RIVF has become an IEEE conference since the IEEE Vietnam Section was formed in 2007. RIVF 2021 is the 15th conference in this series. The RIVF is a premier forum designed for researchers and practitioners to explore cutting-edge ideas, discuss problems, share their research results, identify emerging issues, and establish academic collaborations in various disciplines of computing and communications.

The research team from AIMAI Lab received the best presentation award for the technical paper “Multimodal Fusion with BERT and Attention Mechanism for fake news detection”.

Fake news detection is an important task for increasing the reliability of the information on the Internet since fake news is spreading fast on social media and has a negative effect on our society. In the paper, the research team from AIMAI Lab presented a novel method for detecting fake news by fusing multi-modal features that are derived from textual and visual data. The data fusion process, which is a core technology in multimodal AI, generates important features to improve the accuracy of various AI models. Experimental results in the paper on the MediaEval 2016 dataset showed that the proposed multimodal AI model outperformed existing models in fake news detection.

AIMAI Lab is a research laboratory inside Aimesoft Inc., which focuses on the research and development of Multimodal AI technologies and applications, such as Natural language processing, Speech processing, Computer Vision, and Data mining technologies.