11 citations · 20 across the 5 of their papers we have counts for
5 papers
Mitigating Black-Box Adversarial Attacks via Output Noise Perturbation
Manjushree B. Aithal, Xiaohua Li
In black-box adversarial attacks, adversaries query the deep neural network (DNN), use the output to reconstruct gradients, and then optimize the adversarial inputs iteratively. In…
A Spike Learning System for Event-driven Object Recognition
Shibo Zhou, Wei Wang, Xiaohua Li +1
Event-driven sensors such as LiDAR and dynamic vision sensor (DVS) have found increased attention in high-resolution and high-speed applications. A lot of work has been conducted t…
Temporal Pulses Driven Spiking Neural Network for Fast Object Recognition in Autonomous Driving
Wei Wang, Shibo Zhou, Jingxi Li +3
Accurate real-time object recognition from sensory data has long been a crucial and challenging task for autonomous driving. Even though deep neural networks (DNNs) have been succe…
Deep SCNN-based Real-time Object Detection for Self-driving Vehicles Using LiDAR Temporal Data
Shibo Zhou, Ying Chen, Xiaohua Li +1
Real-time accurate detection of three-dimensional (3D) objects is a fundamental necessity for self-driving vehicles. Most existing computer vision approaches are based on convoluti…
Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding
Jian Zheng, Sudha Krishnamurthy, Ruxin Chen +3
Image captioning has attracted considerable attention in recent years. However, little work has been done for game image captioning which has some unique characteristics and requir…