Road Segmentation Project: Pixel-per-pixel labeling through the use of a Fully Convolutional Neural Network
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Updated
May 28, 2018 - Jupyter Notebook
Road Segmentation Project: Pixel-per-pixel labeling through the use of a Fully Convolutional Neural Network
TensorFlow implementation of Fully Convolutional Networks
Udacity Self Driving Car Semantic Segmentation project
Some models built from scratch with PyTorch during my graduate program at UT Austin
Create a factory function for filling strided arrays with pseudorandom values drawn from a unary PRNG.
Comparison of FCN and CNN on a semantic segmentation task.
[Caffe] A deep convnet developed for semantic segmentation task.
using semantic segmentation to identify drivable path for self driving cars
Implementation of Segnet, FCN, UNet and other models in Keras.
Implement FCN and CNN network using C without Library (use opencv only when reading images)
Create a factory function for filling strided arrays with pseudorandom values drawn from a ternary PRNG.
Add a description, image, and links to the fcn topic page so that developers can more easily learn about it.
To associate your repository with the fcn topic, visit your repo's landing page and select "manage topics."