akenji's lab

In the beginning

In the five articles from this article to this article Galaxy shape(morphological) classification was performed using CNN (VGG16, ResNet) and ViT. In this article, I would like to consider the dataset used for the galaxy morphological classification, as I would like to re-examine the dataset when analyzing errors in the future.

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Introduction.

In this article, we performed galaxy shape classification using the Vision Transformer (ViT) of Transformer’s adaptation to image processing. This time, we performed the same classification using a model already trained as a model for ViT.

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Introduction

In this article at the end of last year, we mentioned that we performed galaxy shape classification with CNN (VGG16, ResNet). In this article, we will perform galaxy shape classification with a Transformer-based Vison Transformer (ViT).

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Introduction

I have been studying Deep Learning for a while and thought I would try it out in my field of interest. I like astronomy and am particularly interested in stellar evolution, the formation of elements, and galaxy formation and evolution. I tried to classify the shape of galaxies, which seemed to be relatively easy to do.

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Continued from previous article.

Why doesn’t the training/testing error improve after repeated epochs? The results of various attempts to answer this question are summarized below.

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Continued from previous article.

In the previous, we studied with VGG16, but this time we will use ResNet for the model.

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Introduction About a month ago, I wrote an article about building a GPU cluster using kubernetes in this article. At that time, the GPU pod was in Pending state and did not work. After that, I managed to get it to work thanks to the advice of a certain person, so I’ll summarize it here. In my environment, there is a problem that the GPU pod does not start up until a certain node is started, and furthermore, I have not been able to specify GPUs in a node, specify nodes, and so on, which is what I assumed, so I decided to call it “the first step”. [Read More]

Motivation Immediately after installing Ubuntu, the display resolution was set to 1368x768. The screen was inconveniently small when working with multiple terminals open, and since I had connected to a display (JAPANNEXT JN-MD-IPS1562FHDR) that can display 1920x1080, I wanted to display it in that resolution. I tried to change the resolution, but got into a bit of trouble, so here is a summary of the process. Sources Ubu [Read More]

Motivation I took on the challenge of creating a GPU cluster using multiple workstations I have set up at home to study Kubernetes. It was a hurdle for me, as I was new to Kubernetes. This is because I had to learn from the documentation whether the operations were necessary only during installation or when building the cluster (during operation). As it stands, the GPU cluster is not operational! This [Read More]

Motivation I had been thinking of the place to compile and store some researches and trials I had done on my field of interest. I decided to use mark downs to describe them, because I’d like to be able to rerecence pages on the internet, display source files such as shell script, and even express formulas. When I was thinking about it, GigHub comes to mind and I decided to store and publish it on GitHub Pages. [Read More]