Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sens...
Recent advances in satellite technology have led to a regular, frequent and high- resolution monitor...
Now a days, deep learning is becoming very famous dueto its power fulability of learning. Deep learn...
The detection of buildings in the city is essential in several geospatial domains and for decision-m...
Traditional building extraction from very high resolution remote sensing optical imagery is limited ...
Very high resolution (VHR) remote sensing imagery has been used for land cover classification, and i...
The rapid growth of the world population has resulted in an exponential expansion of both urban and ...
Building extraction from remote sensing data plays an important role in urban planning, disaster man...
Automatic extraction of buildings from remote sensing images is significant to city planning, popula...
Deep learning (DL) shows remarkable performance in extracting buildings from high resolution remote ...
Deep learning is widely used for the classification of images that have various attributes. Image da...
International audienceThe automated man-made object detection and building extraction from single sa...
International audienceThis work shows how deep learning techniques can benefit to remote sensing. We...
Now a days, deep learning is becoming very famous dueto its power fulability of learning. Deep learn...
Detection of Building edges is crucial for building information extraction and description. Extracti...
Deep Learning has gained much interest recently, probably induced by the re- quirements to learn mor...
Recent advances in satellite technology have led to a regular, frequent and high- resolution monitor...
Now a days, deep learning is becoming very famous dueto its power fulability of learning. Deep learn...
The detection of buildings in the city is essential in several geospatial domains and for decision-m...
Traditional building extraction from very high resolution remote sensing optical imagery is limited ...
Very high resolution (VHR) remote sensing imagery has been used for land cover classification, and i...
The rapid growth of the world population has resulted in an exponential expansion of both urban and ...
Building extraction from remote sensing data plays an important role in urban planning, disaster man...
Automatic extraction of buildings from remote sensing images is significant to city planning, popula...
Deep learning (DL) shows remarkable performance in extracting buildings from high resolution remote ...
Deep learning is widely used for the classification of images that have various attributes. Image da...
International audienceThe automated man-made object detection and building extraction from single sa...
International audienceThis work shows how deep learning techniques can benefit to remote sensing. We...
Now a days, deep learning is becoming very famous dueto its power fulability of learning. Deep learn...
Detection of Building edges is crucial for building information extraction and description. Extracti...
Deep Learning has gained much interest recently, probably induced by the re- quirements to learn mor...
Recent advances in satellite technology have led to a regular, frequent and high- resolution monitor...
Now a days, deep learning is becoming very famous dueto its power fulability of learning. Deep learn...
The detection of buildings in the city is essential in several geospatial domains and for decision-m...