Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

4D: A Real-Time Driver Drowsiness Detector Using Deep Learning

11 references·2 citing·38 second hop

FromToDepth

this work references cited by second hop

References

2010Driver Drowsiness Classification Using Fuzzy Wavelet-Packet-Based Feature-Extraction Algorithm526 cited
2005Fatigue, sleep restriction and driving performance389 cited
2019A Survey on State-of-the-Art Drowsiness Detection Techniques364 cited
2016Towards Detection of Bus Driver Fatigue Based on Robust Visual Analysis of Eye State328 cited
2017Driver Drowsiness Detection via a Hierarchical Temporal Deep Belief Network318 cited
2014YawDD294 cited
2017A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability285 cited
2020Driver Drowsiness Detection Model Using Convolutional Neural Networks Techniques for Android Application213 cited
2011On-Line Detection of Drowsiness Using Brain and Visual Information156 cited
2009Steering Wheel Behavior Based Estimation of Fatigue142 cited
2010A new real-time eye tracking based on nonlinear unscented Kalman filter for monitoring driver fatigue93 cited

Cited by

2024Comprehensive study of driver behavior monitoring systems using computer vision and machine learning techniques93 cited
2024Real-Time Fatigue Detection Algorithms Using Machine Learning for Yawning and Eye State54 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work