Description: Inception score is a metric used to evaluate the quality of images generated by generative adversarial networks (GANs). This metric focuses on two fundamental aspects: diversity and clarity of the generated samples. Diversity refers to the variety of images produced by the model, while clarity assesses how well the details and features of the images are represented. The Inception score is calculated using a pre-trained neural network, such as Inception v3, which classifies the generated images into different categories. From these classifications, a score is obtained that reflects the overall quality of the images. This metric is particularly relevant in the field of artificial intelligence and deep learning, as it allows researchers and developers to compare different models and adjust their parameters to improve the quality of generated images. In summary, the Inception score is a valuable tool for evaluating and optimizing the performance of GANs, providing a quantitative measure that helps guide the development of new architectures and techniques in image generation.
