activity
20202026
most citedAutomatic Classification of Galaxy Morphology: a rotationally invariant supervised machine learning method based on the UML-dataset

34 citations · 82 across the 30 of their papers we have counts for

collaborators
Showing 2025Show all

9 papers · 1 filter

astro-ph.GA2025

A robust morphological classification method for galaxies using dual-encoding contrastive learning and multi-clustering voting on JWST/NIRCam images

Xiaolei Yin, Guanwen Fang, Shiying Lu +3

The two-step galaxy morphology classification framework {\tt USmorph} successfully combines unsupervised machine learning (UML) with supervised machine learning (SML) methods. To e…

astro-ph.GA2025

Robustness Analysis of USmorph: I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification

Shiwei Zhu, Guanwen Fang, Yao Dai +5

We conduct a systematic robustness analysis of the hybrid machine learning framework \texttt{USmorph}, which integrates unsupervised and supervised learning for galaxy morphologica…

astro-ph.GA2025

An updated efficient galaxy morphology classification model based on ConvNeXt encoding with UMAP dimensionality reduction

Guanwen Fang, Shiwei Zhu, Jun Xu +5

We present an enhanced unsupervised machine learning (UML) module within our previous \texttt{USmorph} classification framework featuring two components: (1) hierarchical feature e…

astro-ph.GA2025

Dual-coding contrastive learning based on ConvNeXt and ViT models for morphological classification of galaxies in COSMOS-Web

Shiwei Zhu, Guanwen Fang, Chichun Zhou +4

In our previous works, we proposed a machine learning framework named \texttt{USmorph} for efficiently classifying galaxy morphology. In this study, we propose a self-supervised me…

cs.LG2025

Time-EAPCR-T: A Universal Deep Learning Approach for Anomaly Detection in Industrial Equipment

Huajie Liang, Di Wang, Yuchao Lu +7

With the advancement of Industry 4.0, intelligent manufacturing extensively employs sensors for real-time multidimensional data collection, playing a crucial role in equipment moni…

cs.LG2025

Time-EAPCR: A Deep Learning-Based Novel Approach for Anomaly Detection Applied to the Environmental Field

Lei Liu, Yuchao Lu, Ling An +3

As human activities intensify, environmental systems such as aquatic ecosystems and water treatment systems face increasingly complex pressures, impacting ecological balance, publi…