48 citations · 48 across the 2 of their papers we have counts for
5 papers · 1 filter
Attack Anything: Blind DNNs via Universal Background Adversarial Attack
Jiawei Lian, Shaohui Mei, Xiaofei Wang +5
It has been widely substantiated that deep neural networks (DNNs) are susceptible and vulnerable to adversarial perturbations. Existing studies mainly focus on performing attacks b…
A Comprehensive Study on the Robustness of Image Classification and Object Detection in Remote Sensing: Surveying and Benchmarking
Shaohui Mei, Jiawei Lian, Xiaofei Wang +3
Deep neural networks (DNNs) have found widespread applications in interpreting remote sensing (RS) imagery. However, it has been demonstrated in previous works that DNNs are vulner…
Student Classroom Behavior Detection based on YOLOv7-BRA and Multi-Model Fusion
Fan Yang, Tao Wang, Xiaofei Wang
Accurately detecting student behavior in classroom videos can aid in analyzing their classroom performance and improving teaching effectiveness. However, the current accuracy rate…
CBA: Contextual Background Attack against Optical Aerial Detection in the Physical World
Jiawei Lian, Xiaofei Wang, Yuru Su +2
Patch-based physical attacks have increasingly aroused concerns. However, most existing methods focus on obscuring targets captured on the ground, and some of these methods are sim…
Contextual adversarial attack against aerial detection in the physical world
Jiawei Lian, Xiaofei Wang, Yuru Su +2
Deep Neural Networks (DNNs) have been extensively utilized in aerial detection. However, DNNs' sensitivity and vulnerability to maliciously elaborated adversarial examples have pro…