Mlnd_distracted_driver_detection
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Mlnd_distracted_driver_detection | 98 | 7 years ago | 2 | Jupyter Notebook | ||||||
| 基于深度学习的驾驶员状态检测，不仅仅可以识别出疲劳驾驶，还能够识别出各种各样的状态 | ||||||||||
| Kaggle_distracted_driver | 91 | 5 years ago | 5 | Python | ||||||
| Solutions | ||||||||||
| Drowsydriverdetection | 81 | 6 years ago | 5 | Python | ||||||
| Drowsy driver detection using Keras and convolution neural networks. | ||||||||||
| Computer Vision And Deep Learning Setup | 49 | 4 years ago | 1 | |||||||
| Tutorial on how to setup your system with a NVIDIA GPU and to install Deep Learning Frameworks like TensorFlow, Darknet for YOLO, Theano, and Keras; OpenCV; and NVIDIA drivers, CUDA, and cuDNN libraries on Ubuntu 16.04, 17.10 and 18.04. | ||||||||||
| Drowsydriverdetection | 39 | 6 years ago | 2 | Python | ||||||
| This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy. | ||||||||||
| Poseidon Biwi | 33 | 6 years ago | 8 | Python | ||||||
| A Keras + Theano implementation of my CVPR 2017 paper "POSEidon: Face-from-Depth for Driver Pose Estimation" | ||||||||||
| Da Rnn_manoeuver_anticipation | 16 | 5 years ago | 2 | apache-2.0 | Python | |||||
| Domain-Adaptive Recurrent Neural Network for driving manoeuver anticipation, built in Keras | ||||||||||
| Docker Tensorflow Keras Gpu | 14 | 7 years ago | ||||||||
| Run Tensorflow and Keras with GPU support on Kubernetes | ||||||||||
| Self Driving Robot Using Neural Network | 9 | 3 years ago | mit | Python | ||||||
| This project introduces the autonomous robot which is a scaled down version of actual self-driving vehicle and designed with the help of neural network. The main focus is on building autonomous robot and train it on a designed track with the help of neural network so that it can run autonomously without a controller or driver on that specific track. The robot will stream the video to laptop which will then take decisions and send the data to raspberry pi which will then control the robot using motor driver. This motor driver will move the robot in required directions. Neural Network is used to train the model by first driving the robot on the specially designed track by labeling the images with the directions to be taken. After the model is trained it can make accurate predictions by processing the images on computer. This approach is better than conventional method which is done by extracting specific feature from images. | ||||||||||
| Docker Keras Tensorflow Ubuntu1604 Gpu | 9 | 5 years ago | Dockerfile | |||||||
| Install keras and tensorflow based on cuda 9.0 using docker (python3) and ubuntu1604. Tutorial for installing CUDA driver | ||||||||||
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Jupyter Notebook
Driver
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