6 citations · 16 across the 6 of their papers we have counts for
6 papers
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…
Multi-level Relation Learning for Cross-domain Few-shot Hyperspectral Image Classification
Chun Liu, Longwei Yang, Zheng Li +4
Cross-domain few-shot hyperspectral image classification focuses on learning prior knowledge from a large number of labeled samples from source domains and then transferring the kn…
A novel feature selection framework for incomplete data
Cong Guo
Feature selection on incomplete datasets is an exceptionally challenging task. Existing methods address this challenge by first employing imputation methods to complete the incompl…
Iterative missing value imputation based on feature importance
Cong Guo, Chun Liu, Wei Yang
Many datasets suffer from missing values due to various reasons,which not only increases the processing difficulty of related tasks but also reduces the accuracy of classification.…
Multi-level Cross-modal Feature Alignment via Contrastive Learning towards Zero-shot Classification of Remote Sensing Image Scenes
Chun Liu, Suqiang Ma, Zheng Li +2
Zero-shot classification of image scenes which can recognize the image scenes that are not seen in the training stage holds great promise of lowering the dependence on large number…