5 papers
Generalist Multimodal LLMs Gain Biometric Expertise via Human Salience
Jacob Piland, Byron Dowling, Christopher Sweet +1
Iris presentation attack detection (PAD) is critical for secure biometric deployments, yet developing specialized models faces significant practical barriers: collecting data repre…
VISER: Visually-Informed System for Enhanced Robustness in Iris Presentation Attack Detection
Byron Dowling, Jacob Piland, Eleanor Frederick +2
Human perceptual priors have shown promise in saliency-guided deep learning training, particularly in the domain of iris presentation attack detection (PAD). Common saliency approa…
SAGE: Saliency-Guided Contrastive Embeddings
Colton R. Crum, Christopher Sweet, Adam Czajka
Integrating human perceptual priors into the training of neural networks has been shown to raise model generalization, serve as an effective regularizer, and align models with huma…
Divisive Decisions: Improving Salience-Based Training for Generalization in Binary Classification Tasks
Jacob Piland, Chris Sweet, Adam Czajka
Existing saliency-guided training approaches improve model generalization by incorporating a loss term that compares the model's class activation map (CAM) for a sample's true-clas…
DiffGradCAM: A Class Activation Map Using the Full Model Decision to Solve Unaddressed Adversarial Attacks
Jacob Piland, Chris Sweet, Adam Czajka
Class Activation Mapping (CAM) and its gradient-based variants (e.g., GradCAM) have become standard tools for explaining Convolutional Neural Network (CNN) predictions. However, th…