#Fully-convolutional-networks
Showing 14 of 14 repositories tagged #fully-convolutional-networks, ranked by stars
Semantic Segmentation Architectures Implemented in PyTorch
A Keras port of Single Shot MultiBox Detector
PyTorch for Semantic Segmentation
🚀 😏 Near Real Time CPU Face detection using deep learning
🚘 Easiest Fully Convolutional Networks
Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.
Tensorflow implementation : U-net and FCN with global convolution
Keras implementation of paper by the same name
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images
Light-SERNet: A lightweight fully convolutional neural network for speech emotion recognition
Label-Pixels is the tool for semantic segmentation of remote sensing images using Fully Convolutional Networks. Initially, it is designed for extracting the road network from remote sensing imagery and now, it can be used to extract different features from remote sensing imagery.
[ICCV 2015] Framework for optimizing CNNs with linear constraints for Semantic Segmentation
Recreating PyTorch from scratch, using Numpy. Supports FCN, CNN, RNN layers.
Some of my projects as a former mentor, reviewer, and beta-tester of Robotics and Self-Driving Car ND