https://github.com/ridadogrul/efficientnetb0_for_transfer_learning

https://github.com/ridadogrul/efficientnetb0_for_transfer_learning

efficientnet efficientnetb0 machine-learning stanford-cars transfer-learning

Last synced: 29 days ago
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• Host: GitHub
• URL: https://github.com/ridadogrul/efficientnetb0_for_transfer_learning
• Owner: RidaDogrul
• Created: 2023-08-22T14:33:17.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-08-22T14:41:39.000Z (over 1 year ago)
• Last Synced: 2023-08-22T18:26:03.347Z (over 1 year ago)
• Topics: efficientnet, efficientnetb0, machine-learning, stanford-cars, transfer-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 1.15 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# EfficientNetB0_for_transfer_learning

This is a project for the Stanford Car Classification Challenge on Kaggle. The goal is to classify cars into 196 classes.

The dataset contains 16,185 car images distributed over 196 classes/brands. There are 8,144 images for training and 8,041 images for testing in this dataset. Each class roughly has a 50-50 split in the training and validation set. The dataset is available https://www.kaggle.com/datasets/jutrera/stanford-car-dataset-by-classes-folder

This folder contains results observed from transfer-learning the EfficientNet-b0 model on the Stanford Car dataset.