HasnainRaz/FC-DenseNet-TensorFlow
Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.
This project offers a clear and modular implementation of the Fully Convolutional DenseNet, known as '100 layer tiramisu,' for semantic image segmentation. It takes an image as input and outputs a pixel-wise classification, effectively assigning each pixel to a specific category. This tool is primarily for machine learning researchers and practitioners who want to understand and experiment with this specific neural network architecture.
124 stars. No commits in the last 6 months.
Use this if you are a deep learning researcher or practitioner looking for a highly readable and modular TensorFlow implementation of the FC-DenseNet for semantic image segmentation.
Not ideal if you are looking for a pre-trained, ready-to-use model for image segmentation without needing to understand or modify the underlying network architecture.
Stars
124
Forks
41
Language
Python
License
MIT
Category
Last pushed
Dec 21, 2018
Commits (30d)
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