“Technology News Broadcast: In the field of hyperspectral image classification, experts have proposed an innovative method AL CGNet. This method combines active learning and clustering grouping networks to effectively address the challenges of large network parameters and few labeled samples. AL CGNet reduces the number of parameters through a lightweight network model and improves classification accuracy by utilizing unlabeled sample information. Experimental results have shown that AL CGNet performs well on multiple datasets, significantly improving the efficiency and accuracy of HSI classification, providing strong support for research in related fields.”