… remote sensing image classification techniques, including pixel-wise, sub-pixel-wise, and
object-based image classification … information in remote sensing image classification. Further, …

… of CNN-based remote sensing image classification, and propose corresponding … remote
sensing image classification research and help remote-sensing scientists to tackle classification …

… In this paper, we have presented an active learning framework for remote sensing image
classification. In this framework, the predictor has control on the composition of the training set …

… In remote-sensing image analysis, it … image classification, our goals differ as we wish to
automatically learn contextual features that can help better identify the classes in satellite imagery…

… DL is also taking off in remote sensing image classification most recently, and a growing …
-wise and scene-wise remote sensing image classification approaches that are based on DL…

… way of expressing the accuracy of remote sensing image classifications, such as land cover.
… of error and to visualise the spatial variation in classification uncertainty. This research uses …

… y i i = 1 r donate a set of r remote sensing images, where X i is an image and y i is its … is
composed of 45 classes containing 31,500 remote sensing images. Depending on the data splits …

… in remote sensing image classification: [28] introduces a deep learning algorithm for classification
of (low-dimensional) VHR images; [… class labels for aerial image classification, and [30] …

… the success of remote sensing image classification routines. … remote sensing community
are discussed and some heuristics are detailed and tested. Several challenging remote sensing …

… This work addresses the problem of remote sensing image classification with convolutional
… images, hence new architectures must be designed for dense pixel-wise classification. To …