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handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

hmrf-em

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

hrgeml-v-1

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].

hsi_classification

Classification for hyperspectral imagery

hub

A library for transfer learning by reusing parts of TensorFlow models.

hyperspectral-image-classification-via-fusing-correlation-coefficient-and-joint-sparse-representatio

the code of ''Hyperspectral Image Classification via Fusing Correlation Coefficient and Joint Sparse Representation''

hyperspectral-image-target-detection-based-on-sparse-representation

Hyperspectral image Target Detection based on Sparse Representation

ieee_jstars_rlml

Danfeng Hong, Naoto Yokoya, Xiaoxiang Zhu. Learning a Robust Local Manifold Representation for Hyperspectral Dimensionality Reduction, IEEE JSTARS, 2017.

ieee_tgrs_j-slol

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.

image-edge-detection-based-on-conformal-phase

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.

image-processing-codes-for-easier-understanding

original or modified image processing codes for easier understanding

imageai

A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

imagefusion_dllrr

multi-focus image fusion using dictionary learning and low-rank representation(ICIG 2017, Shanghai)

imagefusionmetrics

imagephasecongruency.jl

Image processing based on image phase information.

interference-detection-and-mitigation-in-automotive-fmcw-radar

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.

interference_mitigation

Automotive Radar Interference Mitigation Using Adaptive Noise Canceller

interferencemitigation_im-sparkle

isprs_lema

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.

isprs_s2fl

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.

j3s

jdsrc

jhesc

Data Representation by Joint Hypergraph Embedding and Sparse Coding

joyful-pandas

Pandas中文教程

jrc

Joint- collective Representation Classification（JRC）;face recognition; 联合稀疏表示分类方法人脸识别

jrl_tcsvt2014

Source code of our TCSVT 2014 paper "Learning Cross-Media Joint Representation with Sparse and Semisupervised Regularization"

jupyter-manim

manim cell magic for IPython/Jupyter to show the output video

kema

code and data for the paper `Kernel Manifold Alignment for domain adaptation'

keras-applications

Reference implementations of popular deep learning models.

keras-complex

Keras-Tensorflow implementation of complex-valued convolutional neural networks