239 citations · 422 across the 13 of their papers we have counts for
6 papers · 1 filter
On the Adversarial Vulnerabilities of Transfer Learning in Remote Sensing
Tao Bai, Xingjian Tian, Yonghao Xu +1
The use of pretrained models from general computer vision tasks is widespread in remote sensing, significantly reducing training costs and improving performance. However, this prac…
AI Security for Geoscience and Remote Sensing: Challenges and Future Trends
Yonghao Xu, Tao Bai, Weikang Yu +3
Recent advances in artificial intelligence (AI) have significantly intensified research in the geoscience and remote sensing (RS) field. AI algorithms, especially deep learning-bas…
Adversarial Purification through Representation Disentanglement
Tao Bai, Jun Zhao, Lanqing Guo +1
Deep learning models are vulnerable to adversarial examples and make incomprehensible mistakes, which puts a threat on their real-world deployment. Combined with the idea of advers…
Inconspicuous Adversarial Patches for Fooling Image Recognition Systems on Mobile Devices
Tao Bai, Jinqi Luo, Jun Zhao
Deep learning based image recognition systems have been widely deployed on mobile devices in today's world. In recent studies, however, deep learning models are shown vulnerable to…
Generating Adversarial yet Inconspicuous Patches with a Single Image
Jinqi Luo, Tao Bai, Jun Zhao
Deep neural networks have been shown vulnerable toadversarial patches, where exotic patterns can resultin models wrong prediction. Nevertheless, existing ap-proaches to adversarial…
Targeting Ultimate Accuracy: Face Recognition via Deep Embedding
Jingtuo Liu, Yafeng Deng, Tao Bai +2
Face Recognition has been studied for many decades. As opposed to traditional hand-crafted features such as LBP and HOG, much more sophisticated features can be learned automatical…