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

no code implementations • 17 May 2024 • Mingxiang Fu, Yu Song, Jiameng Lv, Liang Cao, Peng Jia, Nan Li, Xiangru Li, Jifeng Liu, A-Li Luo, Bo Qiu, Shiyin Shen, Liangping Tu, Lili Wang, Shoulin Wei, Haifeng Yang, Zhenping Yi, Zhiqiang Zou

Hence, as an example to present how to overcome the issue, we built a framework for general analysis of galaxy images, based on a large vision model (LVM) plus downstream tasks (DST), including galaxy morphological classification, image restoration, object detection, parameter extraction, and more.

Astronomy Few-Shot Learning +4

Dynamic Against Dynamic: An Open-set Self-learning Framework

1 code implementation • 27 Apr 2024 • Haifeng Yang, Chuanxing Geng, Pong C. Yuen, Songcan Chen

In particular, a novel self-matching module is designed for OSSL, which can achieve the adaptation in automatically identifying known class samples while rejecting unknown class samples which are further utilized to enhance the discriminability of the model as the instantiated representation of unknown classes.

Open Set Learning Self-Learning

SVM-Lattice: A Recognition & Evaluation Frame for Double-peaked Profiles

no code implementations • 2 May 2020 • Haifeng Yang, Caixia Qu, Jianghui Cai, Sulan Zhang, Xujun Zhao

The DoPS, our previous work [2], provided a search method of rare spectra with double-peaked profiles from massive and high-dimensional data of LAMOST survey.