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Radar-Based Driver Behavior Recognition by fa fa is a document available to read on EtoBox.

The paper presents RFDANet, a radar-based deep learning model that fuses FMCW and TOF radar data to recognize five types of driver behavior with an average accuracy of 94.5%. This method addresses privacy concerns associated with video-based monitoring by utilizing non-intrusive radar technology. The study demonstrates the effectiveness of the proposed model in detecting unsafe driving behaviors, which is crucial for enhancing road safety.

Author
fa fa
Language
EN