Pixel based galaxy morphology classification: Difference between revisions

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Data comes from Legacy Survey in DECaLS region
Data comes from Legacy Survey in DECaLS region
==Labels==
==Labels==
Mike Walmsley trained on DECaLS region with GZD-1/2/5 catalog and GZD-5 class tree with active learning and then form a more confident catalog called catalog_auto. I set a threshold (e.g. 0.5) on each question to split and get labels of each picture. The GZD-5 label tree showed as follows. [[File:GZD-5 Class tree|thumb]]
Mike Walmsley trained on DECaLS region with GZD-1/2/5 catalog and GZD-5 class tree with active learning and then form a more confident catalog called catalog_auto. I set a threshold (e.g. 0.5) on each question to split and get labels of each picture. The GZD-5 label tree showed as follows.
[[File:Tree.png|thumb]]
GZD-5_Class_tree.png
GZD-5_Class_tree.png
==DECaLS introduction==
==DECaLS introduction==

Revision as of 05:17, 6 April 2022

Introduction

This is a project about morphological galaxies classification. The amazing point is that we're researching an algorithm to seperate background and sources for decreasing the pollution.

Dataset

Data comes from Legacy Survey in DECaLS region

Labels

Mike Walmsley trained on DECaLS region with GZD-1/2/5 catalog and GZD-5 class tree with active learning and then form a more confident catalog called catalog_auto. I set a threshold (e.g. 0.5) on each question to split and get labels of each picture. The GZD-5 label tree showed as follows.

Tree.png

GZD-5_Class_tree.png

DECaLS introduction

Out DECaLS introduction

Architecture

  • Simple CNN
  • Dense Net
  • Xception

Loss function

  • Cross Entropy
  • Focal loss

Else

Updating..

Here is the repository on Github