EfficientNet is a family of state-of-the-art convolutional neural networks (CNNs) designed for optimal efficiency in both computation and memory. Developed by Google, it uses a compound scaling method to balance depth, width, and resolution of the network, achieving superior performance on image classification tasks with fewer parameters. EfficientNet variants (e.g., EfficientNet-B0 to B7) are widely adopted in applications like image recognition, object detection, and mobile vision due to their efficiency and accuracy.
