Name: Bobo Xi
Type: User
Company: Xidian University
Bio: I'm currently a Lecturer with the School of Communication Engineering, Xidian University, where I am now focusing on HSI processing and deep learning.
Location: School of Telecommunications Engineering, Xidian University, Xi’an 710071, China 2 South Taibai Road
Blog: https://b-xi.github.io/
Bobo Xi's Projects
Deep learning toolbox based on PyTorch for hyperspectral data classification.
:notebook: deepleaning notes.
Deep Learning Book Chinese Translation
This is a code set for spectral-spatial hyperpsectral classifcation, including the EMAP, Gabor, LORSAL, LibSVM, MRF, and LBP methods.
The Tensorflow implement of the DHCNet
This repository implementates 6 frameworks for hyperspectral image classification based on PyTorch and sklearn.
ECCV 2020 论文开源项目合集,同时欢迎各位大佬提交issue,分享ECCV 2020开源项目
2021年最新总结,推荐工程师合适读本,计算机科学,软件技术,创业,**类,数学类,人物传记书籍
Remote sensed hyperspectral image classification with Spectral-Spatial information provided by the Extended Morphological Profiles
Code for the article 'Hyperspectral Image Classification with Feature-Oriented Adversarial Active Learning'.
A Fast Dense Spectral-Spatial Convolution Network Framework for Hyperspectral Images Classification(FDSSC)
Fractional Gabor Convolutional Network for Multi-source Remote Sensing Data Classification
FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification
A keras based implementation of FuSENet as in paper "Fused Squeeze-and-Excitation Network for Spectral-Spatial Hyperspectral Image Classification"
It's a experiment that applying the graph convolution neural network for hyperspectral image classification
Graph Convolutional Subspace Clustering: A Robust Subspace Clustering Framework for Hyperspectral Image
《深入浅出图神经网络:GNN原理解析》配套代码
Heterogeneous Few-shot Learning for Hyperspectral Image Classification
Source code of "A Single Model CNN for Hyperspectral Image Denoising"
Pytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.
Q. Yuan, Q. Zhang, J. Li, H. Shen, and L. Zhang, "Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network," IEEE TGRS, 2019.
A keras based implementation of Hybrid-Spectral-Net as in IEEE GRSL paper "HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification".
This Toolbox includes Hyperspectral Feature Extraction Techniques including Unsupervised, Supervised, and Deep Feature Extraction
A Deep Learning Classification Framework with Spectral and Spatial Feature Fusion Layers for Hyperspectral and Lidar Sensor Data
Tools for training and using unsupervised autoencoders and supervised deep learning classifiers for hyperspectral data.
Hyperspectral-Classification Pytorch