An emotion driven movie recommendation system.
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Updated
Jun 15, 2024 - Python
An emotion driven movie recommendation system.
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.
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.
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%
Solution to Facial Expression Recognition Kaggle Challenge (FER 2013)
An Emotion Detector Using CNN
A Federated Learning Platform For Facial Expression Recognition using the Flower framework and FER2013 dataset.
Working with the FER2013 dataset, the goal of this assignment was to empirically see and understand the impact of different architectures and hyper-parameters on prediction over the dataset.
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