The rapid development of artificial intelligence (AI) and breakthroughs in Internet of Things
(IoT) technologies have driven the innovation of advanced autonomous driving systems …

Prior research on neural architecture search (NAS) for adversarial robustness has revealed
that a lightweight and adversarially robust sub-network could exist in a non-robust large …

Rice plant lodging recognition is key to improving the performance of weed control
components. However, there are several challenges that cause existing methods to have …

This paper investigates the feasibility of a proactive DeepFake defense framework,{\em
FacePosion}, to prevent individuals from becoming victims of DeepFake videos by …

Annotating data is becoming increasingly important with the prevalence of machine
learning. However, due to limited computing resources and high costs, most data owners …

Adversarial examples represent a serious issue for the application of machine learning
models in many sensitive domains. For generating adversarial examples, decision based …

Artificial Intelligence is a hot topic today, driven by the revolution of neural networks that
have shown impressive performances across various tasks. Notably, in Computer Vision …

Abstract Deep Neural Networks (DNNs) have been proven to be vulnerable to adversarial
attacks. Existing decision-based adversarial attacks require large numbers of queries to find …

The widespread adoption of deep neural networks (DNNs) has raised significant concerns
about their robustness, particularly in real-world environments characterized by inherent …