4 papers
Explicitly Modeling Subcortical Vision with a Neuro-Inspired Front-End Improves CNN Robustness
Lucas Piper, Arlindo L. Oliveira, Tiago Marques
Convolutional neural networks (CNNs) trained on object recognition achieve high task performance but continue to exhibit vulnerability under a range of visual perturbations and out…
Explicitly Modeling Pre-Cortical Vision with a Neuro-Inspired Front-End Improves CNN Robustness
Lucas Piper, Arlindo L. Oliveira, Tiago Marques
While convolutional neural networks (CNNs) excel at clean image classification, they struggle to classify images corrupted with different common corruptions, limiting their real-wo…
Non-Promise Version of Unique Sink Orientations
Tiago Oliveira Marques
A unique sink orientation (USO) is an orientation of the edges of a hypercube such that each face has a unique sink. Many optimization problems like linear programs reduce to USOs,…
Matching the Neuronal Representations of V1 is Necessary to Improve Robustness in CNNs with V1-like Front-ends
Ruxandra Barbulescu, Tiago Marques, Arlindo L. Oliveira
While some convolutional neural networks (CNNs) have achieved great success in object recognition, they struggle to identify objects in images corrupted with different types of com…