Skip to content

About

Image Classification, Image Feature Extraction, CNNs, Finetuning, Resnet18, Torchvision, Multi-Class Logistic Regression

Topics

Resources

Stars

3 stars

Watchers

1 watching

Forks

Latest commit

 

History

6 Commits

Folders and files

NameName
Last commit message
Last commit date
 
 
 
 

Repository files navigation

Image Feature Extraction for Image Classification Using CNN Model, Finetuning and Resnet18 model (From torchvision)

  • Download the CIFAR 10 dataset (original data can be found here, and here is a link to the pickled python version.

  • Use the pretrained Resnet18 model (from trochvision) to extract features. Use the features as inputs in a new multi-class logistic regression model (use nn.Linear/ nn.Module to define your model) -(a) Describe any choices made and report test performance. -(b) Display the top 5 correct predictions and the top 5 incorrect predictions in each class (show the images and the prediction labels) compactly.

  • Finetune the Resnet18 model's parameters suitably and repeat parts (a) and (b) from above. Compare the performance of finetuning versus using extracted features.

About

Image Classification, Image Feature Extraction, CNNs, Finetuning, Resnet18, Torchvision, Multi-Class Logistic Regression

Topics

Resources

Stars

3 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages