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Smart-Traffic-Signals-in-India-using-Deep-Reinforcement-Learning-and-Advanced-Computer-Vision

Ujwal2910 / Smart-Traffic-Signals-in-India-using-Deep-Reinforcement-Learning-and-Advanced-Computer-Vision

Star 182

We have used Deep Reinforcement Learning and Advanced Computer Vision techniques to for the creation of Smart Traffic Signals for Indian Roads. We have created the scripts for using SUMO as our environment for deploying all our RL models.

opencv machine-learning reinforcement-learning deep-learning simulation emulation simulation-environment image-processing deep-reinforcement-learning traffic-analysis video-processing sumo sumologic visionprocessing traffic-simulation shadow-removal indian-traffic smart-traffic-signals rl-agent-learning
  • Updated May 24, 2019
  • Python

Abaco-Systems / jetson-inference-gv

Star 36

This fork of the deep learning guide has been adapted to work with a variety of different inputs USB camera, GigEVision and RTP on the TX1 SoM. This is a a quick demonstrator and example for users of the Abaco Systems rugged Small Form Factor (SFF) TX1 boxed solutions. Please visit out website for more details.

deep-neural-networks computer-vision deep-learning gstreamer neural-network cuda image-recognition segmentation object-detection rtp cudnn visionprocessing nvidia-digits nvidia-jetson-tx1 tensorrt gigevision visionworks
  • Updated May 2, 2017
  • C++

ITU-GeoAI-Challenge / Estimating-Soil-Parameters-from-Hyperspectral-Images-by-ITU-2023

Star 0

The traditional in-situ soil analysis methods are laborious & inefficient, limiting scalability and hindering timely access to crucial soil data for optimal fertilization by farmers. In the amazing challenge, we tried to predict soil parameters(Phosphorous, Potassium, Magnesium and pH)from hyperspectral satellite images. http://tinyurl.com/mw6p25tr

visionprocessing agriculture-research
  • Updated Dec 15, 2023
  • Jupyter Notebook

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