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Found 5 papers, 0 papers with code
Adversarial Attacks Assessment of Salient Object Detection via Symbolic Learning
We test this evolutionary computation methodology against several adversarial attacks and noise perturbations using standard databases and a real-world problem of a shorebird called the Snowy Plover portraying a visual attention task.
Automated Design of Salient Object Detection Algorithms with Brain Programming
This research work proposes expanding the artificial dorsal stream using a recent proposal to solve salient object detection problems.
Brain Programming is Immune to Adversarial Attacks: Towards Accurate and Robust Image Classification using Symbolic Learning
Additionally, the statistical analysis showed that the predictions' confidence of BP were not significantly different for each pair of clean and perturbed images in every experiment.
A Deep Genetic Programming based Methodology for Art Media Classification Robust to Adversarial Perturbations
Therefore, this work presents a Deep Genetic Programming method, called Brain Programming, that competes with deep learning and studies the transferability of adversarial attacks using two artworks databases made by art experts.
It is Time for New Perspectives on How to Fight Bloat in GP
This new perspective allows us to understand that new methods for bloat control can be derived, and the first of such a method is described and tested.
