Hunan Normal University Attract team
Won the "grand space Cup" PIE secondary remote sensing image processing software development contest prize
Title : Remote Sensing Classification System for Advanced Learning - A Case Study of Residential Areas in Changsha classification
Team Profile : Zhou Liang (instructor), Zhang Hui (leader), Deng Yupeng, Liu Yixian, Zhang Chen Road
Synopsis :
Design and Application of this system a small amount of a small amount of high-precision data flag (region of interest), by means of supervised classification or unsupervised classification result to obtain large quantities of data labeled samples, designed to improve the accuracy of remote sensing image. This system can be used to classify multi-band remote sensing image extracted valid data. For example, use of the system for remote sensing image classification Changsha residential area, the better. The system includes basic functions, data processing, intelligent classification, thematic mapping and other functional modules.
Works evaluation :
A good depth study of image classification system, based on PIESDK and TensorFlow, to achieve the extraction of multi-band remote sensing image classification, solved the problem of traditional methods is not easy to get the labels; clear system architecture, advanced algorithms, simple, friendly interface, development more difficult, and supports user-defined Python code, has good scalability; can be used for remote sensing survey of feature identification and water and other resources, practical application and promotion value.
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