1 citations · 1 across the 3 of their papers we have counts for
3 papers
Model Compression Techniques in Biometrics Applications: A Survey
Eduarda Caldeira, Pedro C. Neto, Marco Huber +2
The development of deep learning algorithms has extensively empowered humanity's task automatization capacity. However, the huge improvement in the performance of these models is h…
Compressed Models Decompress Race Biases: What Quantized Models Forget for Fair Face Recognition
Pedro C. Neto, Eduarda Caldeira, Jaime S. Cardoso +1
With the ever-growing complexity of deep learning models for face recognition, it becomes hard to deploy these systems in real life. Researchers have two options: 1) use smaller mo…
Unveiling the Two-Faced Truth: Disentangling Morphed Identities for Face Morphing Detection
Eduarda Caldeira, Pedro C. Neto, Tiago Gonçalves +3
Morphing attacks keep threatening biometric systems, especially face recognition systems. Over time they have become simpler to perform and more realistic, as such, the usage of de…