52 citations · 168 across the 28 of their papers we have counts for
11 papers · 1 filter
Structural-Spectral Graph Convolution with Evidential Edge Learning for Hyperspectral Image Clustering
Jianhan Qi, Yuheng Jia, Hui Liu +1
Hyperspectral image (HSI) clustering groups pixels into clusters without labeled data, which is an important yet challenging task. For large-scale HSIs, most methods rely on superp…
Irregular Tensor Low-Rank Representation for Hyperspectral Image Representation
Bo Han, Yuheng Jia, Hui Liu +1
Spectral variations pose a common challenge in analyzing hyperspectral images (HSI). To address this, low-rank tensor representation has emerged as a robust strategy, leveraging in…
Towards Calibrated Deep Clustering Network
Yuheng Jia, Jianhong Cheng, Hui Liu +1
Deep clustering has exhibited remarkable performance; however, the over confidence problem, i.e., the estimated confidence for a sample belonging to a particular cluster greatly ex…
Superpixel Graph Contrastive Clustering with Semantic-Invariant Augmentations for Hyperspectral Images
Jianhan Qi, Yuheng Jia, Hui Liu +1
Hyperspectral images (HSI) clustering is an important but challenging task. The state-of-the-art (SOTA) methods usually rely on superpixels, however, they do not fully utilize the…
Semi-Supervised Subspace Clustering via Tensor Low-Rank Representation
Yuheng Jia, Guanxing Lu, Hui Liu +1
In this letter, we propose a novel semi-supervised subspace clustering method, which is able to simultaneously augment the initial supervisory information and construct a discrimin…
Deep Attention-guided Graph Clustering with Dual Self-supervision
Zhihao Peng, Hui Liu, Yuheng Jia +1
Existing deep embedding clustering works only consider the deepest layer to learn a feature embedding and thus fail to well utilize the available discriminative information from cl…
Adaptive Attribute and Structure Subspace Clustering Network
Zhihao Peng, Hui Liu, Yuheng Jia +1
Deep self-expressiveness-based subspace clustering methods have demonstrated effectiveness. However, existing works only consider the attribute information to conduct the self-expr…
Attention-driven Graph Clustering Network
Zhihao Peng, Hui Liu, Yuheng Jia +1
The combination of the traditional convolutional network (i.e., an auto-encoder) and the graph convolutional network has attracted much attention in clustering, in which the auto-e…
Superpixel-guided Discriminative Low-rank Representation of Hyperspectral Images for Classification
Shujun Yang, Junhui Hou, Yuheng Jia +2
In this paper, we propose a novel classification scheme for the remotely sensed hyperspectral image (HSI), namely SP-DLRR, by comprehensively exploring its unique characteristics,…
Superpixel Segmentation Based on Spatially Constrained Subspace Clustering
Hua Li, Yuheng Jia, Runmin Cong +3
Superpixel segmentation aims at dividing the input image into some representative regions containing pixels with similar and consistent intrinsic properties, without any prior know…
Maximum Entropy Subspace Clustering Network
Zhihao Peng, Yuheng Jia, Hui Liu +2
Deep subspace clustering networks have attracted much attention in subspace clustering, in which an auto-encoder non-linearly maps the input data into a latent space, and a fully c…