EfficientNet is a convolutional neural network architecture and scaling method that uniformly scales all dimensions of depth/width/resolution using a compound coefficient. Unlike conventional methods that arbitrarily scale these factors, EfficientNet uses a principled approach to find the optimal balance among them. This leads to models that are both smaller and more accurate, achieving state-of-the-art accuracy with significantly fewer parameters and FLOPS. It is commonly used for image classification and object detection tasks.
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