GKalliatakis

PyTorch implementation of the two U-Net-based architectures described in "Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography"

Language:PythonMIT6 30

DisplaceNet

Recognising Displaced People from Images by Exploiting Dominance Level - CVPR '19 Workshop on Computer Vision for Global Challenges (CV4GC)

Language:PythonMIT6 40

Visualising-Facial-Expression-Changes

In order to complete the process of recognising four universal dominant facial expressions (happiness, anger, sadness and surprise), emotion recognition via facial expressions (ERFE) was adopted

Language:JavaScriptMIT5 30

BringDepthDataAlive

Implementation of visualisations presented in the paper ‘Conceiving Human Interaction by Visualising Depth Data of Head Pose Changes and Emotion Recognition via Facial Expressions’

Language:JavaScriptMIT4 30

cheatsheets-ai

Essential Cheat Sheets for deep learning and machine learning researchers

MIT4 20

Human-Rights-UNderstanding-CNNs

Detection of Human Rights Violations in Images: Can Convolutional Neural Networks Help?

3 30

MatDeepRep

A Matlab plugin, built on top of Caffe framework, capable of learning deep representations for image classification using the MATLAB interface – matcaffe & various pretrained caffemodel binaries

Language:MATLABGPL-3.02 30

Keras-EMOTIC-resources

Repo to facilitate the loading process of models trained on EMOTIC

1 20

radimagenet-pytorch

RadImageNet in PyTorch. RadImageNet is an open-access medical imaging database designed for deep learning research and effective transfer learning.

Language:PythonMIT1 30

Traffic-Sign-Recognition-basd-on-Synthesised-Training-Data

Using synthetic data in combination with Deep Learning, to determine if a system can be made that will be able to recognise and classify correctly real traffic signs.

Language:Jupyter NotebookMIT1 20