Producing High Quality Labels through Progressively Improving Strategy

Deep learning has made breakthrough achievements in image classification, object detection, semantic segmentation and other tasks in computer vision. The above results have already promoted the progress of related disciplines. In terms of application, due to the huge differences in the original data, deep learning cannot achieve good results in actual production. The production data is used as the initial sample for network training. With the participation of professionals, a high-precision data set is produced through continuous correction of the sample data and noise removal. Finally, the UpperNet semantic segmentation network was used to classify the area's surface coverage, and the Mean Intersection over Union (mIoU) has reached 85.3%.