1 citations · 1 across the 4 of their papers we have counts for
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…
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…
Augmenting Prototype Network with TransMix for Few-shot Hyperspectral Image Classification
Chun Liu, Longwei Yang, Dongmei Dong +4
Few-shot hyperspectral image classification aims to identify the classes of each pixel in the images by only marking few of these pixels. And in order to obtain the spatial-spectra…