67 citations · 501 across the 27 of their papers we have counts for
13 papers · 1 filter
A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model
Mingxiang Fu, Yu Song, Jiameng Lv +14
The exponential growth of astronomical datasets provides an unprecedented opportunity for humans to gain insight into the Universe. However, effectively analyzing this vast amount…
Dealing with the data imbalance problem on pulsar candidates sifting based on feature selection
Haitao Lin, Xiangru Li
Pulsar detection has become an active research topic in radio astronomy recently. One of the essential procedures for pulsar detection is pulsar candidate sifting (PCS), a procedur…
Galaxy Image Classification using Hierarchical Data Learning with Weighted Sampling and Label Smoothing
Xiaohua Ma, Xiangru Li, Ali Luo +2
With the development of a series of Galaxy sky surveys in recent years, the observations increased rapidly, which makes the research of machine learning methods for galaxy image re…
Estimating Atmospheric Parameters from LAMOST Low-Resolution Spectra with Low SNR
Xiangru Li, Si Zeng, Zhu Wang +3
Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) acquired tens of millions of low-resolution stellar spectra. The large amount of the spectra result in the urgenc…
A Model RRNet for Spectral Information Exploitation and LAMOST Medium-resolution Spectrum Parameter Estimation
Shengchun Xiong, Xiangru Li, Caixiu Liao
This work proposes a Residual Recurrent Neural Network (RRNet) for synthetically extracting spectral information, and estimating stellar atmospheric parameters together with 15 che…
Radio Frequency Interference Mitigation based on the ArPLS and SumThreshold Method
Qingguo Zeng, Xue Chen, Xiangru Li +4
As radio telescopes become sensitive, radio frequency interference (RFI) is more and more serious for interesting signals of radio astronomy. There exist demands for developing an…
Pulsar Candidate Sifting Using Multi-input Convolution Neural Networks
Haitao Lin, Xiangru Li, Qingguo Zeng
Pulsar candidate sifting is an essential process for discovering new pulsars. It aims to search for the most promising pulsar candidates from an all-sky survey, such as High Time R…
Concat Convolutional Neural Network for Pulsar Candidate Selection
Qingguo Zeng, Xiangru Li, Haitao Lin
Pulsar searching is essential for the scientific research in the field of physics and astrophysics. As the development of the radio telescope, the exploding volume and it growth sp…
Pulsars Detection by Machine Learning with Very Few Features
Haitao Lin, Xiangru Li, Ziying Luo
It is an active topic to investigate the schemes based on machine learning (ML) methods for detecting pulsars as the data volume growing exponentially in modern surveys. To improve…
Binary Neutron Stars Gravitational Wave Detection Based on Wavelet Packet Analysis And Convolutional Neural Networks
Baijiong Lin, Xiangru Li, Woliang Yu
This work investigates the detection of binary neutron stars gravitational wave based on convolutional neural network (CNN). To promote the detection performance and efficiency, we…
Stellar Spectra Classification and Feature evaluation Based on Random Forest
Xiangru Li, Yangtao Lin, Kaibin Qiu
With the availability of multi-object spectrometers and the designing \& running of some large scale sky surveys, we are obtaining massive spectra. Therefore, it becomes more and m…
Some Optimizations on Detecting Gravitational Wave Using Convolutional Neural Network
Xiangru Li, Woliang Yu, Xilong Fan +1
This work investigates the problem of detecting gravitational wave (GW) events based on simulated damped sinusoid signals contaminated with white Gaussian noise. It is treated as a…
An autoencoder of stellar spectra and its application in automatically estimating atmospheric parameters
Tan Yang, Xiangru Li
This article investigates the problem of estimating stellar atmospheric parameters from spectra. Feature extraction is a key procedure in estimating stellar parameters automaticall…