most citedLinking convolutional kernel size to generalization bias in face analysis CNNs

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cs.CV2023★ 1 cited

Benchmarking Algorithmic Bias in Face Recognition: An Experimental Approach Using Synthetic Faces and Human Evaluation

Hao Liang, Pietro Perona, Guha Balakrishnan

We propose an experimental method for measuring bias in face recognition systems. Existing methods to measure bias depend on benchmark datasets that are collected in the wild and a…

cs.CV2023★ 1 cited

Linking convolutional kernel size to generalization bias in face analysis CNNs

Hao Liang, Josue Ortega Caro, Vikram Maheshri +2

Training dataset biases are by far the most scrutinized factors when explaining algorithmic biases of neural networks. In contrast, hyperparameters related to the neural network ar…