Alpha-pooling is a new method for improving image recognition in convolutional neural networks. It allows the network to automatically choose the best type of pooling for each task, instead of relying on human experts. By adjusting a parameter called alpha, the network can switch between different pooling methods like max pooling and average pooling. In experiments, alpha-pooling increased accuracy in image recognition tasks, showing that max pooling may not always be the best choice. Each layer in the network may benefit from a different type of pooling.