Remote sensing is mainly used to investigate sites of dams, bridges, and pipelines to locate construction materials and provide detailed geographic information. In remote sensing …
Y Bai, Y Zhao, Y Shao, X Zhang… - International Journal of …, 2022 - Taylor & Francis
In recent years, the combination of deep learning and remote sensing has been a boiling state. However, because of the difference between remote sensing images and natural …
L Zhang, L Zhang, B Du - IEEE Geoscience and remote …, 2016 - ieeexplore.ieee.org
Deep-learning (DL) algorithms, which learn the representative and discriminative features in a hierarchical manner from the data, have recently become a hotspot in the machine …
Deep learning has become one of the most important breakthroughs in artificial intelligence over the past decade. Deep learning contains a variety of methods, including neural …
Remote sensing image scene classification with deep learning (DL) is a rapidly growing field that has gained significant attention in the past few years. While previous review papers …
J Song, S Gao, Y Zhu, C Ma - Big earth data, 2019 - Taylor & Francis
With the development of earth observation technologies, the acquired remote sensing images are increasing dramatically, and a new era of big data in remote sensing is coming …
Developments in remote sensing technology have led to a continuous increase in the volume of remote-sensing data, which can be qualified as big remote sensing data. A wide …
Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social applications. The increase in availability of RS data has …
Scene classification relying on images is essential in many systems and applications related to remote sensing. The scientific interest in scene classification from remotely collected …