Name: Zengfu Hou (侯增福)
Type: User
Company: Beijing Institute of Technology
Bio: PhD, Pattern recognition and Hyperspectral image processing, including anomaly detection, target detection, change detection and object tracking, etc..
Location: Beijing, China
Blog: https://zephyrhours.github.io/
Zengfu Hou (侯增福)'s Projects
This is a demo program for Box-plot figure or statistical separability analysis figure, which can be used for hyperspectral target detection, anomaly detetion or change detection and so on.
Code base for hyperspectral object tracking
A Spectral-Spatial Fusion Anomaly Detection Method for Hyperspectral Imagery
This is the code of paper named "Multipixel Anomaly Detection With Unknown Patterns for Imagery"
Collaborative representation with background purification and saliency weight for hyperspectral anomaly detection
This is the code for the paper nemed 'Anomaly Detection for Hyperspectral Imagery Based on the Regularized Subspace Method and Collaborative Representation'
This is the code for the paper named "Anomaly Detection in Hyperspectral Imagery Based on Low-Rank Representation Incorporating a Spatial Constraint"
Hyperspectral Change Detection Based on Multiple Morphological Profiles
A Patch Tensor-based Change Detection Method for Hyperspectral Images
This is the source codes for this paper called " Spatial-spectral Weighted and Regularized Tensor Sparse Correlation Filter for Object Tracking in Hyperspectral Videos"
Three-Order Tucker Decomposition and Reconstruction Detector for Unsupervised Hyperspectral Change Detection
This is the maximum and minimum morphological feature extraction program for the paper nemed "Hyperspectral Change Detection Based on Multiple Morphological Profiles "
The source code of "Material-Guided Multi-View Fusion Network for Hyperspectral Object Tracking".
[TGRS 2023] The official repo for the paper "Object Detection in Hyperspectral Image via Unified Spectral-Spatial Feature Aggregation".
My personal repository
Dream most deep place, only then the smile is not tired!