This is the code of paper entitled "AFM3D: An Asynchronous Federated Meta-learning Framework for Driver Distraction Detection".
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Updated
Jun 1, 2023 - Python
This is the code of paper entitled "AFM3D: An Asynchronous Federated Meta-learning Framework for Driver Distraction Detection".
Implemantion of a lightweight neural network architecture for the detection of distracted driving among drivers.
Real-time driver distraction detection using time-distributed convolutional LSTM network for mobile platforms
Certainly! The Head-Eye Tracker model consists of several components and functionalities to enable head pose estimation, eye tracking, glasses detection, gaze estimation, and intersection with a 3D representation of the car's interior.
Driver Distraction Detection with CNN and Transfer Learning (VGG19, EfficientNet)
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