PanosAntoniadis

emotion-gcn

[IEEE FG 2021] Official implementation: Exploiting Emotional Dependencies with Graph Convolutional Networks for Facial Expression Recognition

slp-ntua

Lab exercises of Speech and Language Processing course in NTUA

cuda-exercises-ntua

Lab exercise of Parallel Processing course in NTUA regarding CUDA programming

NTUA-ABAW2021

[ICCVW 2021] Official implementation: An audiovisual and contextual approach for categorical and continuous emotion recognition in-the-wild

personalized_asr

[MTAP] Official implementation: A mechanism for personalized Automatic Speech Recognition for less frequently spoken languages: the Greek case

noobcash

Blockchain system created as a part of the Distributed Systems course in NTUA

map_reduce-ntua

Lab exercise of Advanced Topics in Database Systems course in NTUA regarding Map Reduce

pattern_recognition-ntua

Lab exercises of Pattern Recognition course in NTUA

pps-ntua

Lab exercises of Parallel Processing Systems course in NTUA

AI-ntua

Lab exercise of Artificial Intelligence course in NTUA

computer_vision-ntua

Lab exercises of computer vision course in NTUA

dsp-ntua

Lab exercises of Digital Signal Processing course in NTUA

algorithms-ntua

Programming exercises of Algorithms and Complexity course in NTUA

fast-recorder

Simple script that creates a speech dataset quickly

PanosAntoniadis

panosantoniadis.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

SnackDown-2019

Solutions of SnackDown 2019 programming competition hosted by Codechef.

lightning

Build and train PyTorch models and connect them to the ML lifecycle using Lightning App templates, without handling DIY infrastructure, cost management, scaling, and other headaches.

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration