5 citations · 9 across the 4 of their papers we have counts for
5 papers
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks
Anne Harrington, Arturo Deza
Recent work suggests that representations learned by adversarially robust networks are more human perceptually-aligned than non-robust networks via image manipulations. Despite app…
The Effects of Image Distribution and Task on Adversarial Robustness
Owen Kunhardt, Arturo Deza, Tomaso Poggio
In this paper, we propose an adaptation to the area under the curve (AUC) metric to measure the adversarial robustness of a model over a particular -interval (inter…
CUDA-Optimized real-time rendering of a Foveated Visual System
Elian Malkin, Arturo Deza, Tomaso Poggio
The spatially-varying field of the human visual system has recently received a resurgence of interest with the development of virtual reality (VR) and neural networks. The computat…
Hierarchically Compositional Tasks and Deep Convolutional Networks
Arturo Deza, Qianli Liao, Andrzej Banburski +1
The main success stories of deep learning, starting with ImageNet, depend on deep convolutional networks, which on certain tasks perform significantly better than traditional shall…
Assessment of Faster R-CNN in Man-Machine collaborative search
Arturo Deza, Amit Surana, Miguel P. Eckstein
With the advent of modern expert systems driven by deep learning that supplement human experts (e.g. radiologists, dermatologists, surveillance scanners), we analyze how and when d…