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Created over 7 years ago
Updated over 7 years ago

GKalliatakis

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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

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Fourier analysis applications for image matching.

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The wavelet transform and its applications in image denoising

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A simple, multithreaded image scraper implemented in Python for downloading all images from the Flickr web service for a given keyword and time period.

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Deep-Learning-Lecture-Slides

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

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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’

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Human-Rights-UNderstanding-CNNs

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

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A Graphical User Interface (GUI) written in Matlab for recording unlimited frames of video in either .avi files or in Matlab's native format .mat from a USB camera.

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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

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

Python

GKalliatakis/Visualising-Facial-Expression-Changes

GKalliatakis

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