Chaoqi Zhang's Projects
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
A MATLAB implementation of the HMRF as described in "Segmentation of Brain MR Images Through a Hidden Markov Random Field Model and the Expectation-Maximization Algorithm" (Zhang et al., 2001). The HMRF is used to segment images from the cross-sectional OASIS-brains dataset
Updated 31 seconds ago A Matlab implementation of my previous work published in IEEE Trans. Big Data (TBD). If you have any queries, please do not hesitate to contact me at the address below: [email protected].
Classification for hyperspectral imagery
A library for transfer learning by reusing parts of TensorFlow models.
the code of ''Hyperspectral Image Classification via Fusing Correlation Coefficient and Joint Sparse Representation''
Hyperspectral image Target Detection based on Sparse Representation
Danfeng Hong, Naoto Yokoya, Xiaoxiang Zhu. Learning a Robust Local Manifold Representation for Hyperspectral Dimensionality Reduction, IEEE JSTARS, 2017.
Lianru Gao, Danfeng Hong, Jing Yao, Bing Zhang, Paolo Gamba, Jocelyn Chanussot. Spectral Superresolution of Multispectral Imagery with Joint Sparse and Low-Rank Learning, IEEE TGRS, 2020.
To improve the image edge detection accuracy and anti-noise performance, a new approach for image edge detection based on conformal phase is proposed. Firstly, the proposed approach can effectively improve the precision of edge detection and restrain the false edge and noise by using respectively the conformal monogenic signal which could express local structure of the image with different intrinsic dimensions and an exponential function to calculate the phase deviation. Secondly, it can reduce the complexity of the algorithm by taking advantage of the Poisson kernel of existence of analytic representation in spatial domain. To demonstrate the advantages, the proposed approach is compared with the existing methods?of phase congruency based edge?detection. The simulation experiment results show that the proposed approach can extract image edge more accurately, more completely, and more uniformly, with better robustness to noise and lower computational complexity.
original or modified image processing codes for easier understanding
A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities
multi-focus image fusion using dictionary learning and low-rank representation(ICIG 2017, Shanghai)
Image processing based on image phase information.
This is a MATLAB implementation of an algorithm that I proposed to detect and mitigate interference in automotive FMCW RADAR . Please use this source code only for research and academic purposes.
Automotive Radar Interference Mitigation Using Adaptive Noise Canceller
Danfeng Hong, Naoto Yokoya, Nan Ge, Jocelyn Chanussot, Xiaoxiang Zhu. Learnable Manifold Alignment (LeMA): A Semi-supervised Cross-modality Learning Framework for Land Cover and Land Use Classification, ISPRS JP&RS, 2019.
Danfeng Hong, JIngliang Hu, Jing Yao, Jocelyn Chanussot, Xiao Xiang Zhu. Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model, ISPRS JP&RS, 2021.
Data Representation by Joint Hypergraph Embedding and Sparse Coding
Pandas中文教程
Joint- collective Representation Classification(JRC);face recognition; 联合稀疏表示分类方法人脸识别
Source code of our TCSVT 2014 paper "Learning Cross-Media Joint Representation with Sparse and Semisupervised Regularization"
manim cell magic for IPython/Jupyter to show the output video
code and data for the paper `Kernel Manifold Alignment for domain adaptation'
Reference implementations of popular deep learning models.
Keras-Tensorflow implementation of complex-valued convolutional neural networks