simon-xh Goto Github PK

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

caffe2

Caffe2 is a lightweight, modular, and scalable deep learning framework.

cedgan-interpolation

Demo code for the paper -- Spatial interpolation using conditional generative adversarial neural networks

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

deepsegmentor

A Pytorch implementation of DeepCrack and RoadNet projects.

detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

dfo-algorithm

Blackbox derivative-free optimization with DFO-TR algorithm

dl_tutorials

Deep learning tutorials (2nd ed.)

drpnn-deep-residual-pan-sharpening-neural-network

free-programming-books

:books: Freely available programming books

free-programming-books-zh_cn

:books: 免费的计算机编程类中文书籍，欢迎投稿

gmt_docs

GMT中文手册

graphwaveletneuralnetwork

A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)

how-to-make-high-resolution-remote-sensing-image-dataset-

高分遥感影像数据集的制作

hsid-cnn

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.

ica

Independent Component Analysis (for blind source separation)

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-outpainting

Keras Implementation of Painting outside the box

image_cartoonlization

keras

Deep Learning for humans

learnpython

以撸代码的形式学习Python

machine-learning-models

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

markdownoperation.github.io

个人博客

multi-scale-and-depth-cnn-for-pan-sharpening

Matlab implementation of IEEE JSTARS article "A Multiscale and Multidepth Convolutional Neural Network for Remote Sensing Imagery Pan-Sharpening", along with the IEEE GRSL article DRPNN. MatConvNet and Caffe are required for full implementation.

mystudynotes

一些学习笔记

phase-congruency-features

C++ implementation of the phase congruency technique for 2D and 3D data

pointinpolygon

Improved algorithm for determining the inclusion of a point P in a 2D planar polygon. C/C++ implementation.

probabilistic-programming-and-bayesian-methods-for-hackers

Clone of book Probabilistic Programming and Bayesian Methods for Hackers by CamDavidsonPilon

pstcr

Q. Zhang, Q. Yuan, J. Li, Z. Li, H. Shen, and L. Zhang, "Thick Cloud and Cloud Shadow Removal in Multitemporal Images using Progressively Spatio-Temporal Patch Group Learning", ISPRS Journal, 2020.

pyconuk-introtutorial

practical introduction to pandas and scikit-learn via Kaggle problems - Sept 2014