Briefly introduce InceptionV3 model

InceptionV3 is a deep convolutional neural network architecture that was developed by Google researchers in 2015. It is a state-of-the-art image classification model that has achieved high accuracy on various benchmark datasets. The architecture is based on the concept of "inception modules" which are designed to efficiently capture features at different scales and resolutions. InceptionV3 has 48 layers and over 23 million parameters, making it a very powerful model for image recognition tasks. It has been widely used in computer vision applications such as object detection, image segmentation, and visual question answering