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Found 4 papers, 3 papers with code
DSAP: Analyzing Bias Through Demographic Comparison of Datasets
Often, these biases can be traced back to the data used for training, where large uncurated datasets have become the norm.
Metrics for Dataset Demographic Bias: A Case Study on Facial Expression Recognition
One of the most prominent types of demographic bias are statistical imbalances in the representation of demographic groups in the datasets.
Gender Stereotyping Impact in Facial Expression Recognition
Our findings support the need for a thorough bias analysis of public datasets in problems like FER, where a global balance of demographic representation can still hide other types of bias that harm certain demographic groups.
Facial Expression Recognition
Facial Expression Recognition (FER)
Assessing Demographic Bias Transfer from Dataset to Model: A Case Study in Facial Expression Recognition
Of the three metrics proposed, two focus on the representational and stereotypical bias of the dataset, and the third one on the residual bias of the trained model.
Facial Expression Recognition
Facial Expression Recognition (FER)
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