Xuan Zhang · PaperMetrix

Simple Physical Adversarial Examples against End-to-End Autonomous Driving Models

2019 · arXiv (Cornell University)

Recent advances in machine learning, especially techniques such as deep neural networks, are promoting a range of high-stakes applications, including autonomous driving, which often relies on deep learning for perception. While deep learning for perception …

Can Optical Trojans Assist Adversarial Perturbations?

2021

Recent work has demonstrated how physically realizable attacks on neural network vision pipelines can consistently produce misclassifications of a given target object. A smaller body of work has also produced modifications that can be applied …

Graph Capsule Network with a Dual Adaptive Mechanism

2022 · Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

While Graph Convolutional Networks (GCNs) have been extended to various fields of artificial intelligence with their powerful representation capabilities, recent studies have revealed that their ability to capture the part-whole structure of the graph is …

Artificial Intelligence Facial Recognition and Voice Anomaly Detection in the Application of English MOOC Teaching System

2023 · Research Square

Abstract As a direct and effective biometric technology that follows human life habits, facial recognition has gradually become a mainstream, stable and reliable recognition method in the process of further development of science and technology. …

Exploring Body Image Awareness With a Large Language Model–Based Conversational Agent: Qualitative Study With Young Adults (Preprint)

2025

<sec> <title>BACKGROUND</title> Body image plays a crucial role in both physical and mental health, influencing self-esteem, eating behaviors, and psychological well-being. Young adults are particularly vulnerable to body dissatisfaction, defined as negative thoughts or feelings …

Curriculum Learning for Domain Adaptation in Neural Machine Translation

2019