CBANet applies CNN-BiLSTM with attention, SMOTE oversampling, class-weighted loss, and threshold calibration to improve minority-class detection of aggressive driving on a new naturalistic dataset.
Speeding Behavior Estimation Using Stop-and-Go Events Based on Velocity Data
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CBANet: A Compact Attention-Based CNN-BiLSTM Network for Aggressive Driving Event Detection
CBANet applies CNN-BiLSTM with attention, SMOTE oversampling, class-weighted loss, and threshold calibration to improve minority-class detection of aggressive driving on a new naturalistic dataset.