GitHub

Superpixel-based Graph Convolutional Network for Semantic Segmentation

@article{jungsuperpixel, title={Superpixel-based Graph Convolutional Network for Semantic Segmentation}, author={Jung, Hoin and Park, Seong Yeon and Yang, Su and Kim, Jin} } Thie repository is an ...
IEEE

CNN-G: Convolutional Neural Network Combined With Graph for Image Segmentation With ...

Abstract: Deep convolutional neural network (CNN), although recognized to be considerably successful in its application to semantic segmentation, is inadequate for extracting the overall structure ...
GitHub

NVIDIA-accelerated, deep learned semantic image segmentation

Isaac ROS Image Segmentation contains ROS packages for semantic image segmentation. These packages provide methods for classification of an input image at the pixel level by running GPU-accelerated ...
PNAS

Image segmentation with traveling waves in an exactly solvable recurrent neural network

Neural networks are powerful tools for processing visual inputs, but precisely how this processing is performed remains unclear. We introduce a recurrent neural network that can perform simple image ...
Frontiers

Retinal Vessel Segmentation Algorithm Based on Residual Convolution Neural Network

Retinal vessels are the only deep micro vessels that can be observed in human body, the accurate identification of which has great significance on the diagnosis of hypertension, diabetes and other ...
Frontiers

Accurate Tumor Segmentation via Octave Convolution Neural Network

Three-dimensional (3D) liver tumor segmentation from Computed Tomography (CT) images is a prerequisite for computer-aided diagnosis, treatment planning, and monitoring of liver cancer. Despite many ...
Scientific Research Publishing

Food Ingredients Identification from Dish Images by Deep Learning ()

Diet plays an important role in people’s daily life with its strong correlation to health and chronic diseases. Meanwhile, deep based food computing emerges to provide lots of works which including ...