Apr 3, 2019 · Based on transfer learning, we solve the fundamental problem of overfitting due to the inadequate number of labeled remote sensing images by ...
Rapid intelligent detection of airports from remote sensing images is required to accomplish autonomous intelligent landing of unmanned aerial vehicles ...
To address the insufficiency of traditional models in detecting airports under complicated backgrounds from remote sensing images, we propose an end-to-end ...
Li et al [27] built an end-to-end airport detection model from remote sensing images based on a deep transferable convolutional neural network, which overcame ...
This paper presents a method for airport detection from optical satellite images using deep convolutional neural networks (CNN). To achieve fast detection ...
The transfer learning ability of convolutional neural networks (CNNs) has been used to recognize airport runways and airports [15, 16]. CNNs have also been used ...
Sep 21, 2018 · An end-to-end airport detection method based on convolutional neural networks is proposed in this study.
Applying deep-learning technology can considerably improve the efficiency and accuracy of object detection in remote-sensing images (Cannaday et al., 2020, Zeng ...
A fast automatic detection method to detect airports from remote sensing images based on convolutional neural networks using the Faster R-CNN algorithm is ...
Missing: Transferable | Show results with:Transferable
Deep convolutional neural network (CNN) achieves outstanding performance in the field of target detection. As one of the most typical targets in remote sensing ...