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Abnormal driver behavior identification and warning are very important to reduce the rate of road accidents. This is an essential issue as around 1.25 ...
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FDAN: Fuzzy deep attention networks for driver behavior recognition. https://doi.org/10.1016/j.sysarc.2023.103063 ·. Journal: Journal of Systems Architecture ...
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Sep 24, 2024 · Deep learning techniques, particularly Deep Neural Networks (DNN) and CNN , have advanced significantly, improving PAR accuracy and ...
Feb 15, 2023 · In recent years, machine learning and deep learning techniques have accelerated the development of intelligent transport systems (ITS) while ...
A Federated Deep Attention Fusion model is proposed to solve the dual safety problem. •. The SDPAA method is designed to extract the driving process.
Jul 28, 2023 · In this work, we developed a model for predicting dan- gerous driving behavior and conducted experiments using various deep learning methods to ...
Jan 27, 2022 · Following that, the study adopts three deep-learning-based algorithms, namely, Deep Neural Network (DNN), Recurrent Neural Network (RNN), and ...
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This study focuses on a review of the common Li-ion battery aging process and behavior detection methods.
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Jun 10, 2020 · In [16], Deep. Belief Network (DBN) is used to learn and predict speed and steering angle from naturalistic driving data. Driver behavior.
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An Intelligent Multi-Sourced Sensing System to Study Driver's Visual Behaviors · Active Vision-Based Attention Monitoring System for Non-Distracted Driving.