Fully convolutional deep neural network to remove transparent overlays from images
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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
Pixel segmentation of roads from dashboard camera using Fully Convolutional Network
This Project is Semantic Segmentation Project of Term 3 of Udacity Self-Driving Car Engineer Nanodegree.
Neonate segmentation project at NIRAL, UNC, with Dr. Martin Styner.
A real-time application of the LIGHT-SERNET model
using deep learning (semantic segmentation, FCN) to find drivable parts of the road
semantic-segmentation
Labeled the pixels of a road in images using a Fully Convolutional Network (FCN).
Master's thesis
Protein Residue Contact Prediction based on a Deep Neural Architecture
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