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researcher

Chris Sweet

4 papers hereh-index 12 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.LG1

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.LG2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

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