Results 101 to 110 of about 12,268,087 (190)

Semi-Supervised Classification of PolSAR Images Based on Co-Training of CNN and SVM with Limited Labeled Samples. [PDF]

Sensors (Basel), 2023
Zhao M, Cheng Y, Qin X, Yu W, Wang P.
europepmc   +1 more source

Self-Paced Convolutional Neural Network for PolSAR Images Classification

, 2019
Fully polarimetric synthetic aperture radar (PolSAR) can transmit and receive electromagnetic energy on four polarization channels (HH, HV, VH, VV). The data acquired from four channels have both similarities and complementarities.
Changzhe Jiao, Wenshuai Chen, Debo Li, Chao Chen, Xiaofeng Li, Xinlin Wang, Shuiping Gou   +6 more
core   +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

Classification of PolSAR Image Using Neural Nonlocal Stacked Sparse Autoencoders with Virtual Adversarial Regularization

, 2019
Polarimetric synthetic aperture radar (PolSAR) has become increasingly popular in the past two decades, for it can derive multichannel features of ground objects, which contains more discriminative information compared with traditional SAR. In this paper,
Ruichuan Wang, Yanfei Wang
core   +1 more source

A Deep Learning Classification Scheme for PolSAR Image Based on Polarimetric Features

Polarimetric features extracted from polarimetric synthetic aperture radar (PolSAR) images contain abundant back-scattering information about objects.
Lizhen Cui, Shuaiying Zhang, Zhen Dong, Wentao An   +3 more
core   +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

CCDR: Combining Channel-Wise Convolutional Local Perception, Detachable Self-Attention, and a Residual Feedforward Network for PolSAR Image Classification

In the task of PolSAR image classification, effectively utilizing convolutional neural networks and vision transformer models with limited labeled data poses a critical challenge.
Haifeng Sima, Zhaozhao Xu, Junding Sun, Jianlong Wang, Bingjie Zhang   +4 more
core   +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

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