Results 121 to 130 of about 2,015 (220)

Land Use and Land Cover Classification Meets Deep Learning: A Review. [PDF]

Sensors (Basel), 2023
Zhao S, Tu K, Ye S, Tang H, Hu Y, Xie C.
europepmc   +1 more source

Segmentation of multi-temporal polarimetric SAR data based on mean-shift and spectral graph partitioning. [PDF]

PeerJ, 2022
Wang C, Zhao L, Zhang W, Mu X, Li S.
europepmc   +1 more source

BSDSNet: Dual-Stream Feature Extraction Network Based on Segment Anything Model for Synthetic Aperture Radar Land Cover Classification

Remote Sensing
Land cover classification using high-resolution Polarimetric Synthetic Aperture Radar (PolSAR) images obtained from satellites is a challenging task. While deep learning algorithms have been extensively studied for PolSAR image land cover classification,
Yangyang Wang, Wengang Zhang, Weidong Chen, Chang Chen   +3 more
doaj   +1 more source

Supervised PolSAR Image Classification with Multiple Features and Locally Linear Embedding. [PDF]

Sensors (Basel), 2018
Zhang Q, Wei X, Xiang D, Sun M.
europepmc   +1 more source

MCDiff: A Multilevel Conditional Diffusion Model for PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
With the swift advancement of deep learning, significant strides have been made in polarimetric synthetic aperture radar (PolSAR) image classification, particularly with the advent of diffusion models that allow for explicit class probability modeling ...
Qingyi Zhang, Xiaoxiao Fang, Tao Liu, Ronghua Wu, Liguo Liu, Chu He   +5 more
doaj   +1 more source

Perceptually Optimal Color Representation of Fully Polarimetric SAR Imagery. [PDF]

J Imaging, 2022
Koukiou G.
europepmc   +1 more source

Gaofen-3 PolSAR Image Classification via XGBoost and Polarimetric Spatial Information. [PDF]

Sensors (Basel), 2018
Dong H, Xu X, Wang L, Pu F.
europepmc   +1 more source

Multiple Classifiers Based Semi-Supervised Polarimetric SAR Image Classification Method. [PDF]

Sensors (Basel), 2021
Zhu L, Ma X, Wu P, Xu J.
europepmc   +1 more source

PolSAR image classification with Binary Partition Tree

, 2017
The objective of this project is to study new techniques in the use of Binary Partition Tree to improve the classification of objects in PolSAR images. Different techniques will be developed and the results will be compared with the state of the art. Finally, some conclusions are presented and some possible lines of future work are discussed.
openaire   +1 more source

PolSAR Image Classification Via a Multigranularity Hybrid CNN-ViT Model With External Tokens and Cross-Attention

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
With the development of deep learning technology, the application of convolutional neural network (CNN) and vision transformer (ViT) for polarimetric synthetic aperture radar (PolSAR) image classification has been deepened.
Wenke Wang, Jianlong Wang, Dou Quan, Meijuan Yang, Junding Sun, Bibo Lu   +5 more
doaj   +1 more source