The mobile learning system will not only bring the attention of students towards education but also higher results can be achieved. One of the motives of the research is to involve the students in... Show More

The mobile learning system will not only bring the attention of students towards education but also higher results can be achieved. One of the motives of the research is to involve the students in their academic assignment by using a system that lets the students work on the assignment with interest. Moreover, better results from students are expected after implementing the mobile learning system. Manual work will be given to students before the mobile learning system to get the attention of students and then work on the mobile learning system will be assigned. The difference between both traditional and computerization mobile learning systems will be analyzed by surveying students. The traditional cloud computing structure is physically centralized.

For the massive large-scale visible image data obtained by satellite, unmanned aerial vehicles, and other reconnaissance platforms, if only relying on manual visual interpretation, there will be... Show More

For the massive large-scale visible image data obtained by satellite, unmanned aerial vehicles, and other reconnaissance platforms, if only relying on manual visual interpretation, there will be problems such as heavy workload, low efficiency, high repeatability, strong subjectivity, and high cost, which cannot meet the demand of modern society for efficient information. Therefore, in order to improve work efficiency, it is necessary to study the rapid automatic region localization in large-scale remote sensing images. That will play an important role in change detection, temperature retrieval, and other files. The development and present situation of the region localization algorithms are analyzed. This paper summarizes the development, improvement, and deficiency of the traditional algorithm, as well as the difficulties and challenges. And the authors make a comparison to the deep learning-based methods. Finally, a possible development direction is prospected.