https://www.selleckchem.com/products/tapi-1.html
The strong training set are then used as pseudo-labels to reclassify the weak dataset by CV-CNN. The final classification results are obtained by combining the strong training set and the reclassification results. Experiments on two real PolSAR images on agricultural and forest areas indicate that, in most cases, significant improvements can be achieved with the proposed method, compared to the base classifiers, and the improvement is approximately 3-5%. When the number of labeled samples was small, the superiority of the proposed method
Like
Comment
Share
