Multimodal Fusion of Telecom and Vision-based Data for Scalable Traffic Prediction
We leverage extensive mobile telecom data, integrated with sparse vision data, to provide comprehensive traffic insights. First, we utilize telecom data from widespread road sections as a novel traffic indicator while ensuring user privacy. Next, for the first time, we enhance traffic prediction accuracy by fusing telecom data with camera-based vision data. To further optimize performance, we propose a multi-modal framework that balances the influence of different data modalities, enabling precise cross-modal predictions. This research progress has been recognized by top conferences such as AAAI, WWW, and CIKM.
Building integrated management system by artificial intelligence based on big data analysis and data mining to implement precision medicine in healthcare management
Collection and Analysis of Crowdsourced Data Based on Randomized Response for Compliance Personal Data Protection Act
Design and Implementation of Mining Purchasing Datasets for Purchasing Behavior Prediction and EDM Title Generation
"1) Integrating AI recognition, IoT, and blockchain into traceable software and hardware for recycling UCO 2) Cutting-edge 3D learning platform powered by Spatial AI 3) Optimize use of existing buildings by making them transformable and adaptive to human needs at the click of a button 4) Non-contact image analysis and calculation technology to capture vital signs through dynamic face detection"
Technology maturity：Experiment stage
Exhibiting purpose：Display of scientific results
Trading preferences：Negotiate by self
Coming soon!