Fully convolutional deep neural network to remove transparent overlays from images
-
Updated
Mar 29, 2021 - Python
Fully convolutional deep neural network to remove transparent overlays from images
Multi-Planar UNet for autonomous segmentation of 3D medical images
An API that detect expiration date from the product package's picture based on Deep Learning Algorithms
A robot motion planning simulator that can efficiently navigate partially observable environments using deep learning
Protein Residue Contact Prediction based on a Deep Neural Architecture
semantic-segmentation
Neonate segmentation project at NIRAL, UNC, with Dr. Martin Styner.
Master's thesis
This Project is Semantic Segmentation Project of Term 3 of Udacity Self-Driving Car Engineer Nanodegree.
Labeled the pixels of a road in images using a Fully Convolutional Network (FCN).
using deep learning (semantic segmentation, FCN) to find drivable parts of the road
Pixel segmentation of roads from dashboard camera using Fully Convolutional Network
A real-time application of the LIGHT-SERNET model
Add a description, image, and links to the fully-convolutional-network topic page so that developers can more easily learn about it.
To associate your repository with the fully-convolutional-network topic, visit your repo's landing page and select "manage topics."