Enhancing CNNs robustness to occlusions with bioinspired filters for border completion
arXiv:2504.17619
Abstract
We exploit the mathematical modeling of the visual cortex mechanism for border completion to define custom filters for CNNs. We see a consistent improvement in performance, particularly in accuracy, when our modified LeNet 5 is tested with occluded MNIST images.
Submitted to the 7th International Conference on Geometric Science of Information