Fast Automatic Airport Detection in Remote Sensing Images Using Convolutional Neural Networks
Fast and automatic detection of airports from remote sensing images is useful for many military and civilian applications. In this paper, a fast automatic detection method is proposed to detect airports from remote sensing images based on convolutional neural networks using the Faster R-CNN algorith...
Main Authors: | Fen Chen, Ruilong Ren, Tim Van de Voorde, Wenbo Xu, Guiyun Zhou, Yan Zhou |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-03-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | http://www.mdpi.com/2072-4292/10/3/443 |
Similar Items
-
Airport Detection Using End-to-End Convolutional Neural Network with Hard Example Mining
by: Bowen Cai, et al.
Published: (2017-11-01) -
Airport Cluster Delay Prediction Based on TS-BiLSTM-Attention
by: Xiujie Wei, et al.
Published: (2023-06-01) -
An Attention-Based Deep Convolution Network for Mining Airport Delay Propagation Causality
by: Xianghua Tan, et al.
Published: (2022-10-01) -
Airports and automation /
by: World Airports Conference (9th : 1991 : London), et al.
Published: (1992) -
Airport planning/
by: 287092 Froesch, Charles, et al.