4 papers
Generating Transferrable Adversarial Examples via Local Mixing and Logits Optimization for Remote Sensing Object Recognition
Chun Liu, Hailong Wang, Bingqian Zhu +5
Deep Neural Networks (DNNs) are vulnerable to adversarial attacks, posing significant security threats to their deployment in remote sensing applications. Research on adversarial a…
Adversarial Patch Attack for Ship Detection via Localized Augmentation
Chun Liu, Panpan Ding, Zheng Zheng +5
Current ship detection techniques based on remote sensing imagery primarily rely on the object detection capabilities of deep neural networks (DNNs). However, DNNs are vulnerable t…
Few-shot Unknown Class Discovery of Hyperspectral Images with Prototype Learning and Clustering
Chun Liu, Chen Zhang, Zhuo Li +2
Open-set few-shot hyperspectral image (HSI) classification aims to classify image pixels by using few labeled pixels per class, where the pixels to be classified may be not all fro…
Boosting Adversarial Transferability for Hyperspectral Image Classification Using 3D Structure-invariant Transformation and Weighted Intermediate Feature Divergence
Chun Liu, Bingqian Zhu, Tao Xu +5
Deep Neural Networks (DNNs) are vulnerable to adversarial attacks, which pose security challenges to hyperspectral image (HSI) classification based on DNNs. Numerous adversarial at…