ResNet50_on_Cifar_100_Without_Transfer_Learning

Code

• github.com/batuhan3526/ResNet50_on_Cifar_100_Without_Transfer_Learning
  none★ 16
• github.com/2023-MindSpore-1/ms-code-217/tree/main/ssd_resnet50
  mindspore★ 0
• github.com/Mind23-2/MindCode-69
  mindspore★ 0
• github.com/2023-MindSpore-1/ms-code-217/tree/main/ssc_resnet50
  mindspore★ 0
• github.com/2023-MindSpore-4/Code7/tree/main/ssc_resnet50
  mindspore★ 0
• github.com/2023-MindSpore-4/Code7/tree/main/ssd_resnet50
  mindspore★ 0

Abstract

I am a young person who is curious about image classification. I have an average knowledge and an average computer. I thought the cifar 100 data for image classification was challenging for me. It was a data containing 100 classes from 32x32 and 100 images. I chose resnet as the model due to the low number of data and gradient vanishing problem. I worked with google colab because my computer is not enough (thank you Google) Since I used the free version, I could only run Resnet50. I tried to stick to the original Resnet article. But I made it myself in changes. I have tried many hyper parameters. I found the parameters that gave the best results as soon as possible as fast as I could. I'm a young man who likes to push his luck. that is all

Tasks

Reproductions