Emotion detection using CNN

zainab Bukhari

In this project, we developed an emotion detection system using Convolutional Neural Networks (CNN) to accurately classify human emotions from facial expressions. Leveraging a dataset of labeled facial images, we trained a CNN model to recognize and categorize emotions such as happiness, sadness, anger, and surprise. The model architecture includes multiple convolutional layers for feature extraction, followed by fully connected layers for classification. This approach enables real-time emotion detection with high accuracy, making it suitable for applications in human-computer interaction, mental health monitoring, and customer service enhancement.
Like this project

Posted Sep 19, 2024

In this project, we developed an emotion detection system using Convolutional Neural Networks (CNN) to accurately classify human emotions from facial expression

Prediction Of Preeclampsia Using Machine Learning Model
Prediction Of Preeclampsia Using Machine Learning Model

Drone Swarming as network-controlled systems.
Drone Swarming as network-controlled systems.