Retraction Note: Image detection of mountain soil loss and human avoidance trajectory based on cloud computing and machine learning

Abstract

With the continuous progress and development of modern social science management and network security technology in China, the wide application of new-generation technologies such as intelligent robotics learning has made it more and more extensive in the field of analysis. At present, it has fully played an important technical leading role in many application fields, such as analysis methods, collection and sorting ability, analysis of various large-scale business computing application statistical data of enterprises, mining theoretical knowledge of natural environment science, image recognition, retrieval of global geographic location information and so on. Through the simulation of soil erosion in mountainous areas in my country, dynamic data analysis describes the basic situation of soil erosion in various mountainous areas in my country and the whole process of its evolution and development and comprehensively analyzes and studies various soil erosion events in mountainous areas in my country. The corresponding solutions can effectively and accurately respond to emergencies of soil erosion in mountainous areas and effectively reduce the loss of soil and water crops and economic losses in natural disasters. In recent years, information technology companies related to computer and machine learning capabilities, especially based on machine cloud computing, learning science and technology based on the theory of human machine artificial intelligence, and combining related professional technologies, have been used in various areas to prevent floods, droughts, risks, and rain in various areas. Disaster reduction and other non-natural engineering construction technology prevention measures have gradually been applied. The main research question of this paper is to design a related human body trajectory image detection system for new human facial image processing based on machine learning, and information collection and detection management system, and conduct in-depth research on its application prospects.