ACCOR: Novel AI Approach Improves Object Classification with mmWave Radar

This research explores a novel application of contrastive learning, specifically tailoring it to the nuances of mmWave radar data for object classification under occlusion. The focus on complex-valued data and attention mechanisms suggests a sophisticated approach to extracting relevant features from noisy sensor signals.

• •Applies attention-enhanced contrastive learning to mmWave radar data.
• •Focuses on improving object classification under occlusion.
• •Utilizes complex-valued data for signal processing.