SqueezeNet is a compact and efficient deep learning model for image classification. This project demonstrates the use of SqueezeNet, which achieves AlexNet-level accuracy with fewer parameters. The repository includes an implementation of SqueezeNet for image classification tasks on datasets like ImageNet. The project also demonstrates how to deploy SqueezeNet on edge devices with limited computational resources, making it suitable for real-time applications.
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