Pinned Repositories
awesome-affective-computing
A curated list of awesome affective computing 🤖❤️ papers, software, open-source projects, and resources
AWESOME-FER
Top conferences & Journals focused on FER/FAU 😠😣😨😀🙁😯😑
Awesome-Graph-Neural-Networks
Paper Lists for Graph Neural Networks
Challenge-condition-FER-dataset
This is our collected datasets for challenge condition facial expression recognition
emotion-recognition-neural-networks
Emotion recognition using DNN with tensorflow
face.evoLVe.PyTorch
🔥🔥High-Performance Face Recognition Library on PyTorch🔥🔥
facial-expression-recognition-using-cnn
Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions from images or camera stream
GOAL-CR
This project is concerned with computing channel access strategies that minimize the expected contention resolution time in single-hop random access networks. The uncertainty in the contention is addressed by modeling the problem as a partially observable stochastic game. A Reinforcement Learning method is implemented to find approximately optimal solutions. In addition, a novel algorithm was developed to compute optimal strategies in more efficient running time.
IW276SS20P2
Affective Computing - Face Expression Recognition
ltp
Language Technology Platform
okokyou's Repositories
okokyou/awesome-affective-computing
A curated list of awesome affective computing 🤖❤️ papers, software, open-source projects, and resources
okokyou/AWESOME-FER
Top conferences & Journals focused on FER/FAU 😠😣😨😀🙁😯😑
okokyou/Awesome-Graph-Neural-Networks
Paper Lists for Graph Neural Networks
okokyou/Challenge-condition-FER-dataset
This is our collected datasets for challenge condition facial expression recognition
okokyou/emotion-recognition-neural-networks
Emotion recognition using DNN with tensorflow
okokyou/face.evoLVe.PyTorch
🔥🔥High-Performance Face Recognition Library on PyTorch🔥🔥
okokyou/facial-expression-recognition-using-cnn
Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions from images or camera stream
okokyou/GOAL-CR
This project is concerned with computing channel access strategies that minimize the expected contention resolution time in single-hop random access networks. The uncertainty in the contention is addressed by modeling the problem as a partially observable stochastic game. A Reinforcement Learning method is implemented to find approximately optimal solutions. In addition, a novel algorithm was developed to compute optimal strategies in more efficient running time.
okokyou/IW276SS20P2
Affective Computing - Face Expression Recognition
okokyou/ltp
Language Technology Platform
okokyou/MULTIMODAL-EMOTION-RECOGNITION
Human Emotion Understanding using multimodal dataset.
okokyou/pornhubbot
基于Python3的pornhub网站爬虫
okokyou/Prediction-and-Localization-of-Student-Engagement-in-the-Wild
Using Deep Multi Instance Learning to localize Student Engagement Level during watching education videos.