A human emotion recognition based learning assistant. HACKOH/IO - 2019
The purpose of this project was to simply test a CNN model on a competition FER2013 dataset.
This GitHub repository hosts a Facial Emotion Recognition project that utilizes Convolutional Neural Networks (CNNs) to detect emotions from facial expressions in real-time. Built with Python, TensorFlow, Keras, and OpenCV, the project includes scripts for training the emotion detection model using the FER 2013 dataset and testing it with live webc
FER model uses Convolutional Neural Network algorithm trained on FER2013 dataset to recognize five universal emotions of the Facial Action Coding System. It can detect multiple faces with exceptionally outstanding results. (IEEE Published)
An emotion driven movie recommendation system.
Tackling facial emotion recognition (FER) tasks using DCNNs, VGG16 and Inception-V3 models
An academic research project for comparative analysis of deep learning models in facial emotion recognition.
Using Keras (Tensorflow), CNN and OpenCV, this model accurately identifies emotions from facial expressions in real-time video streams.
An emotion detection CNN-based model that can detect emotions from images in real-time
A ready-to-use Facial Expression Recognition model using MobileNet on augmented FER2013 dataset. Val accuracy > 89%
Emotion Detection using deep unbaised CNN!!
This project implements deep learning models for classifying images. Using TensorFlow and Keras, it includes scripts and notebooks for training and testing neural networks on various datasets to achieve high accuracy in image categorization.
Product Market Analysis is a software that allows Companies to receive reviews on their products from Beta Testers by using Deep Learning to detect facial expressions.
A website that performs facial emotion analysis on uploaded images using AI!
A Deep Learning model deployed with FastAPI recognizes emotions using facial expression.
A implementation for facial expression recognition on fer2013 dataset using Residual Masking Network architecture
It intergrate a custom built pure cnn based facial emotion recogtion model with accuracy of 64% in a web that implements technology like webRTC and asunchronous js.
The goal of facial expression detection is to accurately identify the emotions expressed by a person's face.
Graduation project
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