5 citations · 5 across the 8 of their papers we have counts for
11 papers
Patch-based Querying Identifies Structures of Interest in Electron Microscopy
Niels Vyncke, Nicolas Nadisic, Yvan Saeys +1
Volume electron microscopy (vEM) has emerged as an essential sensing technique in biomedical research, allowing the three-dimensional imaging of biological cells and tissues at nan…
Aligned Consensus Teaching for Label-Efficient Oriented Object Detection in Weakly-Aligned Visible-Infrared Imagery
Qi Ming, Xiaxin Yuan, Jiahuan Zhou +6
Visible-infrared object detection (VIOD) detects objects with oriented bounding boxes from paired visible and infrared images. Existing methods depend on costly dual-modality annot…
InterPruner: Interactive Structured Pruning via Taylor-Implicit Criterion and Language-Prior Modulator for Multimodal Object Detection
Qi Ming, Zihan Yang, Shaoguang Huang +6
Multimodal object detection proves effective in remote sensing, especially the RGB-Infrared paradigm. The parallel feature extractors provide rich multimodal information for robust…
Anatomically Conditioned Recurrent Refinement for Topology-Aware Circle of Willis Segmentation
Juraj Perić, Marija Habijan, Dario Mužević +3
Segmenting the Circle of Willis (CoW) from Magnetic Resonance Angiography (MRA) is challenging due to complex topology and thin vascular structures that are prone to fragmentation.…
An Enhanced Geometric-Spectral Feature Learning Framework for Airborne Multispectral Point Cloud Classification
Xian Li, Yanfeng, Gu Linghua Xu +1
Multispectral point cloud (MPC) is composed of 3D spatial-spectral information, which holds tremendous potential for accurate land-cover classification. However, the representation…
Joint Superpixel and Self-Representation Learning for Scalable Hyperspectral Image Clustering
Xianlu Li, Nicolas Nadisic, Shaoguang Huang +1
Subspace clustering is a powerful unsupervised approach for hyperspectral image (HSI) analysis, but its high computational and memory costs limit scalability. Superpixel segmentati…
Generalized Category Discovery in Hyperspectral Images via Prototype Subspace Modeling
Xianlu Li, Nicolas Nadisic, Shaoguang Huang +1
Generalized category discovery~(GCD) seeks to jointly identify both known and novel categories in unlabeled data. While prior works have mainly focused on RGB images, their assumpt…
Scalable Context-Preserving Model-Aware Deep Clustering for Hyperspectral Images
Xianlu Li, Nicolas Nadisic, Shaoguang Huang +2
Subspace clustering has become widely adopted for the unsupervised analysis of hyperspectral images (HSIs). Recent model-aware deep subspace clustering methods often use a two-stag…
An Enhanced Classification Method Based on Adaptive Multi-Scale Fusion for Long-tailed Multispectral Point Clouds
TianZhu Liu, BangYan Hu, YanFeng Gu +2
Multispectral point cloud (MPC) captures 3D spatial-spectral information from the observed scene, which can be used for scene understanding and has a wide range of applications. Ho…
Unfolding ADMM for Enhanced Subspace Clustering of Hyperspectral Images
Xianlu Li, Nicolas Nadisic, Shaoguang Huang +1
Deep subspace clustering methods are now prominent in clustering, typically using fully connected networks and a self-representation loss function. However, these methods often str…
OsmLocator: locating overlapping scatter marks with a non-training generative perspective
Yuming Qiu, Aleksandra Pizurica, Qi Ming +1
Automated mark localization in scatter images, greatly helpful for discovering knowledge and understanding enormous document images and reasoning in visual question answering AI sy…