Results 81 to 90 of about 505 (177)

PolSAR Image Classification Based on Multi-Modal Contrastive Fully Convolutional Network

Remote Sensing
Deep neural networks have achieved remarkable results in the field of polarimetric synthetic aperture radar (PolSAR) image classification. However, PolSAR is affected by speckle imaging, resulting in PolSAR images usually containing a large amount of ...
Wenqiang Hua, Yi Wang, Sijia Yang, Xiaomin Jin   +3 more
doaj   +1 more source

A Novel Multi-Objective Binary Chimp Optimization Algorithm for Optimal Feature Selection: Application of Deep-Learning-Based Approaches for SAR Image Classification. [PDF]

Sensors (Basel), 2023
Sadeghi F, Larijani A, Rostami O, Martín D, Hajirahimi P.   +4 more
europepmc   +1 more source

A Deep Similarity Clustering Network With Compound Regularization for Unsupervised PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Polarimetric synthetic aperture radar (PolSAR) image classification is a critical application of remote sensing image interpretation. Most of the early algorithms that use hand-crafted features to divide the image into various scattering categories have ...
Yixin Zuo, Guangzuo Li, Wenjuan Ren, Yuxin Hu   +3 more
doaj   +1 more source

PCCN: Polarimetric Contexture Convolutional Network for PolSAR Image Super-Resolution

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Polarimetric synthetic aperture radar (PolSAR) can acquire full-polarization information, which is the solid foundation for target scattering mechanism interpretation and utilization. Meanwhile, PolSAR image resolution is usually lower than the synthetic
Lin-Yu Dai, Ming-Dian Li, Si-Wei Chen
doaj   +1 more source

Marine Oil Spill Detection from SAR Images Based on Attention U-Net Model Using Polarimetric and Wind Speed Information. [PDF]

Int J Environ Res Public Health, 2022
Chen Y, Wang Z.
europepmc   +1 more source

Heterogeneous Network-Based Contrastive Learning Method for PolSAR Land Cover Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Polarimetric synthetic aperture radar (PolSAR) image interpretation is widely used in various fields. Recently, deep learning has made significant progress in PolSAR image classification. Supervised learning (SL) requires a large amount of labeled PolSAR
Jianfeng Cai, Yue Ma, Zhixi Feng, Shuyuan Yang, Licheng Jiao   +4 more
doaj   +1 more source

Self-Trained Deep Forest with Limited Samples for Urban Impervious Surface Area Extraction in Arid Area Using Multispectral and PolSAR Imageries. [PDF]

Sensors (Basel), 2022
Liu X, Samat A, Li E, Wang W, Abuduwaili J.   +4 more
europepmc   +1 more source

A Dense Bootstrap Contrastive Learning Method With 3-D Dynamic Convolution for Few-Shot PolSAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
High-quality labeled samples of polarimetric synthetic aperture radar (PolSAR) images are relatively scarce. Therefore, achieving optimal classification performance with limited labeled samples has become a significant challenge in PolSAR image ...
Nana Jiang, Wenbo Zhao, Jiao Guo, Xiuya Dong, Jubo Zhu   +4 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

A PolSAR Image Segmentation Algorithm Based on Scattering Characteristics and the Revised Wishart Distance. [PDF]

Sensors (Basel), 2018
Yi H, Yang J, Li P, Shi L, Lang F.
europepmc   +1 more source