Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging
Explainable artificial intelligence (XAI) has experienced a vast increase in recognition over
the last few years. While the technical developments are manifold, less focus has been …
the last few years. While the technical developments are manifold, less focus has been …
[HTML][HTML] Adversarial attack and defence through adversarial training and feature fusion for diabetic retinopathy recognition
Due to the rapid growth in artificial intelligence (AI) and deep learning (DL) approaches, the
security and robustness of the deployed algorithms need to be guaranteed. The security …
security and robustness of the deployed algorithms need to be guaranteed. The security …
[PDF][PDF] Adversarial machine learning
Abstract This NIST Trustworthy and Responsible AI report develops a taxonomy of concepts
and defines terminology in the field of adversarial machine learning (AML). The taxonomy is …
and defines terminology in the field of adversarial machine learning (AML). The taxonomy is …
Evidential dissonance measure in robust multi-view classification to resist adversarial attack
Multi-view learning is effective in improving data classification accuracy through integrating
information from multiple sources. To guarantee the reliability of multi-view classification, the …
information from multiple sources. To guarantee the reliability of multi-view classification, the …
Quantifying and enhancing multi-modal robustness with modality preference
Multi-modal models have shown a promising capability to effectively integrate information
from various sources, yet meanwhile, they are found vulnerable to pervasive perturbations …
from various sources, yet meanwhile, they are found vulnerable to pervasive perturbations …
Map: Multispectral adversarial patch to attack person detection
Recently, multispectral person detection has shown great performance in real world
applications such as autonomous driving and security systems. However, the reliability of …
applications such as autonomous driving and security systems. However, the reliability of …
Hardening RGB-D object recognition systems against adversarial patch attacks
RGB-D object recognition systems improve their predictive performances by fusing color and
depth information, outperforming neural network architectures that rely solely on colors …
depth information, outperforming neural network architectures that rely solely on colors …