Semi Supervised Learning For Image Captioning

Using semi-supervised learning for image caption generation is a machine learning approach that combines a small amount of labeled data with a large amount of unlabeled data. The goal is to optimize the model's ability to learn from the labeled data while leveraging the structural information in the unlabeled data, thereby improving the accuracy and richness of image descriptions. This technique has significant application value in the field of computer vision, effectively reducing annotation costs and enhancing model generalization capabilities. It is applicable to scenarios such as image content understanding and visual question answering.