Shao Wujun's repositories
ADS_NASA
ADS_NASA
ads_test
This code queries the number of articles per year that give the limit through the API, and the citations of all articles are accumulated.
Astronomical-object-detection
Classifying Astronomical objects using SDSS - DR16 Data
Astrostatistics2022
Python samples for Astrostatistics 2022 Spring
Classification-of-Astronomical-Objects
This project's goal is to classify sky objects such as star, galaxy, and quasar via sdss data.
cv-arxiv-daily
🎓Automatically Update CV Papers Daily using Github Actions (Update Every 12th hours)
Document-Layout-Analysis
Tools for extract figure, table, text, .. from a pdf document.
get_publications
Retrieves, formats and prints publication library from NASA ADS in a LaTeX-friendly format
hanlaomao
Config files for my GitHub profile.
LAMOST-
LAMOST光谱分类的一些程序
MatlabFunc
Matlab codes for feature learning
ML-NOTE
:orange_book:慢慢整理所学的机器学习算法，并根据自己所理解的样子叙述出来。(注重数学推导)
poe-api-wrapper
👾 A Python API wrapper for Poe.com, using Httpx. With this, you will have free access to ChatGPT, Claude, Llama, Google-PaLM and more! 🚀
pylamost
Python interface for LAMOST Data
Python
All Algorithms implemented in Python
random-forest-outlier
Outlier detection algorithm for MaNGA data built upon the Unsupervised Random Fores (URF) in Dalya Baron, Dovi Poznanski, The weirdest SDSS galaxies: results from an outlier detection algorithm, Monthly Notices of the Royal Astronomical Society, Volume 465, Issue 4, March 2017, Pages 4530–4555, https://doi.org/10.1093/mnras/stw3021
sdss-analysis-and-classification
Sloan Digital Sky Survey exploratory analysis, classification model selection and parameter optimization using genetic algorithms.
SDSS-ML
These scripts explore galaxy/quasar/star classification from optical and infrared magnitudes using supervised machine learning.
SDSS-ML-classification
Analyse the catalogue data of DR-14, 15 & 16 to understand the differences in the spectra of the three classes of celestial objects, namely stars, galaxies, and quasars, using Machine learning techniques
SDSS-VAE
Dimensionality Reduction of SDSS Spectra with Variational Autoencoders
Stellar-Classification-SDSS17
A stellar dataset from Kaggle analysed, pre-processed and four models (SVM, Random Forest, KNN & Logistic Regression) are made with accuracies over 95%.
TableNet
Unofficial implementation of "TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images"
WaldoInSky
Code Repository for `Where is Waldo (and his friends)? A comparison of anomaly detection algorithms for time-domain astronomy`
WeirdestGalaxies
This repository contains the basic outlier detection algorithm that we use to find the weirdest SDSS galaxies.