Unmanned aerial vehicle for remote sensing applications—A review
H Yao, R Qin, X Chen - Remote Sensing, 2019 - mdpi.com
The unmanned aerial vehicle (UAV) sensors and platforms nowadays are being used in
almost every application (eg, agriculture, forestry, and mining) that needs observed …
almost every application (eg, agriculture, forestry, and mining) that needs observed …
Deep learning-based semantic segmentation of urban features in satellite images: A review and meta-analysis
Availability of very high-resolution remote sensing images and advancement of deep
learning methods have shifted the paradigm of image classification from pixel-based and …
learning methods have shifted the paradigm of image classification from pixel-based and …
ResUNet-a: A deep learning framework for semantic segmentation of remotely sensed data
Scene understanding of high resolution aerial images is of great importance for the task of
automated monitoring in various remote sensing applications. Due to the large within-class …
automated monitoring in various remote sensing applications. Due to the large within-class …
Deepglobe 2018: A challenge to parse the earth through satellite images
Abstract We present the DeepGlobe 2018 Satellite Image Understanding Challenge, which
includes three public competitions for segmentation, detection, and classification tasks on …
includes three public competitions for segmentation, detection, and classification tasks on …
Beyond RGB: Very high resolution urban remote sensing with multimodal deep networks
In this work, we investigate various methods to deal with semantic labeling of very high
resolution multi-modal remote sensing data. Especially, we study how deep fully …
resolution multi-modal remote sensing data. Especially, we study how deep fully …
Land cover map** at very high resolution with rotation equivariant CNNs: Towards small yet accurate models
In remote sensing images, the absolute orientation of objects is arbitrary. Depending on an
object's orientation and on a sensor's flight path, objects of the same semantic class can be …
object's orientation and on a sensor's flight path, objects of the same semantic class can be …
Water body classification from high-resolution optical remote sensing imagery: Achievements and perspectives
Water body classification from high-resolution optical remote sensing (RS) images, aiming at
classifying whether each pixel of the image is water or not, has become a hot issue in the …
classifying whether each pixel of the image is water or not, has become a hot issue in the …
Road segmentation in SAR satellite images with deep fully convolutional neural networks
Remote sensing is extensively used in cartography. As transportation networks grow and
change, extracting roads automatically from satellite images is crucial to keep maps up-to …
change, extracting roads automatically from satellite images is crucial to keep maps up-to …
TreeUNet: Adaptive tree convolutional neural networks for subdecimeter aerial image segmentation
Fine-grained semantic segmentation results are typically difficult to obtain for subdecimeter
aerial imagery segmentation as a result of complex remote sensing content and optical …
aerial imagery segmentation as a result of complex remote sensing content and optical …
Building extraction based on U-Net with an attention block and multiple losses
M Guo, H Liu, Y Xu, Y Huang - Remote Sensing, 2020 - mdpi.com
Semantic segmentation of high-resolution remote sensing images plays an important role in
applications for building extraction. However, the current algorithms have some semantic …
applications for building extraction. However, the current algorithms have some semantic …