Picture for Xiangru Li

Xiangru Li

A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model

Add code
May 17, 2024
Figure 1 for A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model
Figure 2 for A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model
Figure 3 for A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model
Figure 4 for A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model
Viaarxiv icon

Multi-Prompt Fine-Tuning of Foundation Models for Enhanced Medical Image Segmentation

Add code
Oct 03, 2023
Viaarxiv icon

Galaxy Image Classification using Hierarchical Data Learning with Weighted Sampling and Label Smoothing

Add code
Dec 20, 2022
Figure 1 for Galaxy Image Classification using Hierarchical Data Learning with Weighted Sampling and Label Smoothing
Figure 2 for Galaxy Image Classification using Hierarchical Data Learning with Weighted Sampling and Label Smoothing
Figure 3 for Galaxy Image Classification using Hierarchical Data Learning with Weighted Sampling and Label Smoothing
Figure 4 for Galaxy Image Classification using Hierarchical Data Learning with Weighted Sampling and Label Smoothing
Viaarxiv icon

Estimation of stellar atmospheric parameters from LAMOST DR8 low-resolution spectra with 20$\leq$SNR$<$30

Add code
Apr 13, 2022
Figure 1 for Estimation of stellar atmospheric parameters from LAMOST DR8 low-resolution spectra with 20$\leq$SNR$<$30
Figure 2 for Estimation of stellar atmospheric parameters from LAMOST DR8 low-resolution spectra with 20$\leq$SNR$<$30
Figure 3 for Estimation of stellar atmospheric parameters from LAMOST DR8 low-resolution spectra with 20$\leq$SNR$<$30
Figure 4 for Estimation of stellar atmospheric parameters from LAMOST DR8 low-resolution spectra with 20$\leq$SNR$<$30
Viaarxiv icon

Pulsars Detection by Machine Learning with Very Few Features

Add code
Feb 20, 2020
Figure 1 for Pulsars Detection by Machine Learning with Very Few Features
Figure 2 for Pulsars Detection by Machine Learning with Very Few Features
Figure 3 for Pulsars Detection by Machine Learning with Very Few Features
Figure 4 for Pulsars Detection by Machine Learning with Very Few Features
Viaarxiv icon

Linearly Supporting Feature Extraction For Automated Estimation Of Stellar Atmospheric Parameters

Add code
Apr 10, 2015
Figure 1 for Linearly Supporting Feature Extraction For Automated Estimation Of Stellar Atmospheric Parameters
Figure 2 for Linearly Supporting Feature Extraction For Automated Estimation Of Stellar Atmospheric Parameters
Figure 3 for Linearly Supporting Feature Extraction For Automated Estimation Of Stellar Atmospheric Parameters
Figure 4 for Linearly Supporting Feature Extraction For Automated Estimation Of Stellar Atmospheric Parameters
Viaarxiv icon