A survey of mobile laser scanning applications and key techniques over urban areas
Urban planning and management need accurate three-dimensional (3D) data such as light
detection and ranging (LiDAR) point clouds. The mobile laser scanning (MLS) data, with up …
detection and ranging (LiDAR) point clouds. The mobile laser scanning (MLS) data, with up …
Combining Sentinel-1 and Sentinel-2 Satellite Image Time Series for land cover mapping via a multi-source deep learning architecture
The huge amount of data currently produced by modern Earth Observation (EO) missions
has allowed for the design of advanced machine learning techniques able to support …
has allowed for the design of advanced machine learning techniques able to support …
Siamese convolutional neural networks for remote sensing scene classification
The convolutional neural networks (CNNs) have shown powerful feature representation
capability, which provides novel avenues to improve scene classification of remote sensing …
capability, which provides novel avenues to improve scene classification of remote sensing …
DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn
Abstract Nowadays, modern Earth Observation systems continuously generate huge
amounts of data. A notable example is represented by the Sentinel-2 mission, which …
amounts of data. A notable example is represented by the Sentinel-2 mission, which …
AFNet: Adaptive fusion network for remote sensing image semantic segmentation
R Liu, L Mi, Z Chen - IEEE Transactions on Geoscience and …, 2020 - ieeexplore.ieee.org
Semantic segmentation of remote sensing images plays an important role in many
applications. However, a remote sensing image typically comprises a complex and …
applications. However, a remote sensing image typically comprises a complex and …
Local semantic enhanced convnet for aerial scene recognition
Aerial scene recognition is challenging due to the complicated object distribution and spatial
arrangement in a large-scale aerial image. Recent studies attempt to explore the local …
arrangement in a large-scale aerial image. Recent studies attempt to explore the local …
Multi-sensor image fusion: a survey of the state of the art
B Li, Y Xian, D Zhang, J Su… - Journal of …, 2021 - research.europeanlibrarypress.com
Image fusion has been developing into an important area of research. In remote sensing, the
use of the same image sensor in different working modes, or different image sensors, can …
use of the same image sensor in different working modes, or different image sensors, can …
All grains, one scheme (AGOS): Learning multigrain instance representation for aerial scene classification
Aerial scene classification remains challenging as: 1) the size of key objects in determining
the scene scheme varies greatly and 2) many objects irrelevant to the scene scheme are …
the scene scheme varies greatly and 2) many objects irrelevant to the scene scheme are …
Polarimetric convolutional network for PolSAR image classification
The approaches for analyzing the polarimetric scattering matrix of polarimetric synthetic
aperture radar (PolSAR) data have always been the focus of PolSAR image classification …
aperture radar (PolSAR) data have always been the focus of PolSAR image classification …
A spatial-channel progressive fusion ResNet for remote sensing classification
In recent years, the panchromatic (PAN) and the multispectral (MS) remote sensing images
classification has become a research hotspot. In this paper, we propose a spatial-channel …
classification has become a research hotspot. In this paper, we propose a spatial-channel …