Maximum Likelihood Classification of Soil Remote Sensing Image Based on Deep Learning

Deep Learning-Based Classification of Remote Sensing Image

Deep Learning networks have sharply increased over the past 10 years, and deep Learning-Based Classification of Remote Sensing Image has attracted extensive interest. We trained a multilayer deep learning network to classify the 8 thousand unlabeled remote sensing images from Internet into the 600 different classes. In order to improve the efficiency, and shorten the experiment time, we also us...

Deep Self-taught Learning for Remote Sensing Image Classification

This paper addresses the land cover classification task for remote sensing images by deep self-taught learning. Our selftaught learning approach learns suitable feature representations of the input data using sparse representation and undercomplete dictionary learning. We propose a deep learning framework which extracts representations in multiple layers and use the output of the deepest layer ...

Remote Sensing Image Classification

Research of Forest Classification Based on Remote Sensing Image

The forest plays an important role in regulating climate and improving ecological carrying capacity. In view of heterogeneous mixed young afforestation, the object-based classification on rules method is used to identify the types of planted forest, combined with spectrum, texture and shape characteristics information. ESP tool was applied to obtain the best segmentation scale and the rule set ...

Remote Sensing Image Classification Based on Gray System Theory

The intelligence and automation of image processing and analysis is a bottle problem for photogrammetry and remote sensing. Artificial neural networks is a new solver which imitates brain and gray system theory is a new tool which handles undetermined problem. This paper describe how to combine artificial neural networks with gray system theory to realize classification of remote sensing image ...