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A Survey of Vision Models For CIFAR-10
Abstract
In this report, We explore the existing deep learning solutions for the single object classification computer vision problem. We compare the current state-of-the-art transformer based models that are capable of zero-shot learning to deep residual networks or ResNets fine-tuned using transfer learning. We provide an x-ray summary of both architectures, as well as discuss tractability and applicability issues.
Team Members
- Shwetima Sakshi
- Muhammed Ersoy
- Goutham Kolaparthi
- Shaunak Joshi
- Howie Morgenthaler
Installation
pip install -r requirements.txt
Running The Code
python main.py <train|test> --model <clip|vit|resnext|svm> --device <cuda|cpu>
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