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Facial Expression/ Recognition dataset of Human Beings.
Train a neural network to recognize facial expressions using a dataset from Kaggle. Learn the basics of image classification and computer vision in this beginner-friendly project. Explore the code ...
Mar 2, 2024 · One such benchmark dataset for training models to recognise facial expressions is FER2013. This dataset comprises 35,887 grayscale facial images, each measuring 48 by 48 pixels,...
5 days ago · Facial expression recognition system is an advanced technology that allows machines to recognize human emotions based on their facial expressions. ... and Kaggle to compile a comprehensive dataset ...
Fer2013 contains approximately 30,000 facial RGB images of different expressions with size restricted to 48×48, and the main labels of it can be divided into 7 types: 0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral.
The dataset can be downloaded from : https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/data. The data consists of 48x48 pixel grayscale images of faces.
Mar 3, 2020 · Face Images with Marked Landmark Points is a Kaggle dataset to predict keypoint positions on face images. Size: The size of the dataset is 497MP and contains 7049 facial images and up to 15 key points marked on them.
We trained and tested our models on the data set from the Kaggle Facial Expression Recognition Challenge, which comprises 48-by-48-pixel grayscale images of human faces,each labeled with one of 7 emotion categories: anger, disgust, fear, happiness, sadness, surprise, and neutral .
Jul 1, 2021 · AffectNet is by far the largest database of facial expression, valence, and arousal in the wild enabling research in automated facial expression recognition in two different emotion models.
