Landslide detection is concerned with delineating the extent of landslides. Most existing works on landslide have limited geographical extents. Therefore, models developed out these studies might perform poorly when applied to regions different characteristics. This study investigates an Object-Based Image Analysis methodology built unsupervised and supervised Machine Learning detect location l...

Mineral image classification technology based on machine vision is an efficient system for ore sorting. With the development of artificial intelligence and computer technology, deep learning-based mineral gradually applied to However, there a bottleneck in improving accuracy, feature extraction ability CNNs model relatively limited multi-category tasks. Therefore, four visual attention blocks a...

Most work in reinforcement learning (RL) is based on discounted techniques, such as Q learning, where long-term rewards are geometrically attenuated based on the delay in their occurence. Schwartz recently proposed an undiscounted RL technique called R learning that optimizes average reward, and argued that it was a better metric than the discounted one optimized by Q learning. In this paper we...

Introduction: Blended learning, a new approach in educational planning, isdefined as an applying more than one method, strategy, technique or media in education. Todays, due to the development of infrastructure of Internet networks and the access of most of the students, the Internet can be utilized along with traditional and conventional methods of training. The aim of this study was to compar...