Search Results for author:
Found 6 papers, 0 papers with code
The AI Security Pyramid of Pain
Data Provenance is the next critical layer, ensuring the authenticity and lineage of data and models.
Adversarial Attack Attribution: Discovering Attributable Signals in Adversarial ML Attacks
In other words, is there a way to find a signal in these attacks that exposes the attack algorithm, model architecture, or hyperparameters used in the attack?
Image quality assessment for determining efficacy and limitations of Super-Resolution Convolutional Neural Network (SRCNN)
Traditional metrics for evaluating the efficacy of image processing techniques do not lend themselves to understanding the capabilities and limitations of modern image processing methods - particularly those enabled by deep learning.
Leveraging synthetic imagery for collision-at-sea avoidance
We present our results on the use of synthetic imagery in a computer vision based collision-at-sea warning system with promising performance.
Ship classification from overhead imagery using synthetic data and domain adaptation
In this paper, we revisit the problem of classifying ships (maritime vessels) detected from overhead imagery.
Generative NeuroEvolution for Deep Learning
A significant approach to addressing this gap has been machine learning approaches that are inspired from the natural systems, such as artificial neural networks (ANNs), evolutionary computation (EC), and generative and developmental systems (GDS).
