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 2023Show all

5 papers · 1 filter

cs.CV2023

Simple but Effective Unsupervised Classification for Specified Domain Images: A Case Study on Fungi Images

Zhaocong liu, Fa Zhang, Lin Cheng +4

High-quality labeled datasets are essential for deep learning. Traditional manual annotation methods are not only costly and inefficient but also pose challenges in specialized dom…

cs.CV2023

A 3M-Hybrid Model for the Restoration of Unique Giant Murals: A Case Study on the Murals of Yongle Palace

Jing Yang, Nur Intan Raihana Ruhaiyem, Chichun Zhou

The Yongle Palace murals, as valuable cultural heritage, have suffered varying degrees of damage, making their restoration of significant importance. However, the giant size and un…

astro-ph.GA2023

The Classification of Galaxy Morphology in H-band of COSMOS-DASH Field: a combination-based machine learning clustering model

Yao Dai, Jun Xu, Jie Song +6

By applying our previously developed two-step scheme for galaxy morphology classification, we present a catalog of galaxy morphology for H-band selected massive galaxies in the COS…

cs.CV2023★ 1 cited

Human-machine knowledge hybrid augmentation method for surface defect detection based few-data learning

Yu Gong, Xiaoqiao Wang, Chichun Zhou

Visual-based defect detection is a crucial but challenging task in industrial quality control. Most mainstream methods rely on large amounts of existing or related domain data as a…

eess.IV2023★ 1 cited

A Data Augmentation Method and the Embedding Mechanism for Detection and Classification of Pulmonary Nodules on Small Samples

Yang Liu, Yue-Jie Hou, Chen-Xin Qin +4

Detection of pulmonary nodules by CT is used for screening lung cancer in early stages.omputer aided diagnosis (CAD) based on deep-learning method can identify the suspected areas…