Briefly introduce the EfficientNet model

The EfficientNet model is a convolutional neural network architecture that was designed to achieve state-of-the-art accuracy while minimizing the number of parameters and computational resources required for training and inference. It uses a combination of depth-wise convolution, squeeze-and-excitation blocks, and compound scaling to achieve high accuracy on a variety of image classification tasks. The EfficientNet model has been shown to outperform other popular CNN architectures such as ResNet and Inception on several benchmark datasets