Analyzing Biases in Visual Recognition Models

Jaspreet Ranjit
With the rise of deep learning models which require exceedingly large amounts of data, there exists a need to examine the biases that are reflected in the applications of these models. For example, a visual recognition model can learn image representations of cooking that are closer to the representations of women than men, thus reinforcing a negative gender stereotype of women being homemakers. This thesis explores and analyzes these biases across state of the art...
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