Chengcheng2016's repositories
awesome-graph-classification
A collection of important graph embedding, classification and representation learning papers with implementations.
bagging-boosting-random-forests
Bagging, boosting and random forests in Matlab
BicycleGAN
[NIPS 2017] Toward Multimodal Image-to-Image Translation
DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
gaussian-mixture-models
implementation of expectation maximization algorithm for gaussian mixture models and comparing it with non-parametric histogram estimation
GG-Rician-SAR-Image-Modelling
A Rician distribution based novel statistical model for modelling the intensity and amplitude SAR images
GNN_Review
GNN综述阅读报告
Grabcut
This a project to implement the algorithm of GrabCut
hyperspectral-image-classification
Hyperspectral Image (HSI) classification with matlab
IEEE_TGRS_GCN
Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot. Graph Convolutional Networks for Hyperspectral Image Classification, IEEE TGRS, 2020.
IGARSS2020_BWMS
Codes for IGARSS2020 paper: Band-Wise Multi-Scale CNN Architecture for Remote Sensing Image Scene Classification.
matconvnet-18
MatConvNet: CNNs for MATLAB
matresnet
Residual networks with MatConvNet
MTCNN_face_detection_alignment
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks
Multi-scale-CNN-based-MRF-for-image-segmentation
The code is for image segmentation. The MSCNN.py is implemented using keras with tensorflow as backend. The *.m files are implemented on MATLAB.
Non-Linear-Classifier
Classification of handwritten MNIST data using SVM, RVM, Gaussian process model
PatternRecognition_Matlab
Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of classification algorithm are implemented: Support Vector Machine (SVM), Gaussian Quadratic Maximum Likelihood and K-nearest neighbors (KNN) and Gaussian Mixture Model(GMM).
poldecomp
Polarimetric Synthetic Aperture Radar (PolSAR) Decomposition Modelling
SAR-Synthetic-Aperture-Radar
合成孔径雷达 相关。研究生期间学习 SAR/InSAR/PolSAR 相关的代码和总结，毕业后已经离开这个领域了。分享出来，仅此纪念。1）SAR: 成像算法，RD，CS，Radarsat-1数据成像处理。2）InSAR: 人造场景原始回波仿真、成像及干涉处理。包括平地场景和圆锥形场景。3）PolSAR: 极化定标算法，Whitt, PARC, Quegan, Ainsworth。详见 readme.md
semi_supervised_learning_tutorial
Tutorial presentation and code showing a semi-supervised Gaussian Mixture Model
Seven-Component-Scattering-Power-Decomposition-of-POLSAR-Coherency-Matrix
Singh's Seven-Component Scattering Power Decomposition
sgmm
Supervised Gaussian Mixture Models
source_code
I share the source codes of my previously published papers.
SSAN
Spectral-Spatial Attention Network for Hyperspectral Image Classification
sumproduct
Sum product algorithm - Belief propagation (message passing) for factor graphs