https://github.com/arindam-modak/robust-lane-detection-in-hazy-environment-using-encoder-decoder-cnn-lstm-dcp

Robust Lane Detection in hazy/foggy environment using Encoder Decoder CNN & LSTM and Dark Channel Prior to tackle with hazy environemnt
https://github.com/arindam-modak/robust-lane-detection-in-hazy-environment-using-encoder-decoder-cnn-lstm-dcp

convlstm dark-channel-prior dcnn encoder-decoder google-colab image-segmentation image-transformations neural-networks segnet tusimple-dataset

Last synced: about 2 months ago
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Robust Lane Detection in hazy/foggy environment using Encoder Decoder CNN & LSTM and Dark Channel Prior to tackle with hazy environemnt

• Host: GitHub
• URL: https://github.com/arindam-modak/robust-lane-detection-in-hazy-environment-using-encoder-decoder-cnn-lstm-dcp
• Owner: arindam-modak
• Created: 2019-10-11T13:45:23.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-01-01T09:15:12.000Z (over 5 years ago)
• Last Synced: 2024-03-20T17:06:50.147Z (about 1 year ago)
• Topics: convlstm, dark-channel-prior, dcnn, encoder-decoder, google-colab, image-segmentation, image-transformations, neural-networks, segnet, tusimple-dataset
• Language: Jupyter Notebook
• Homepage:
• Size: 16.7 MB
• Stars: 4
• Watchers: 3
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# Robust-Lane-Detection-using-Encoder-Decoder-CNN-LSTM

Robust Lane Detection in hazy/foggy environment using Encoder Decoder CNN & LSTM and Dark Channel Prior to tackle with hazy environemnt.