Results 81 to 90 of about 11,244,032 (159)

Auto Encoder Feature Learning with Utilization of Local Spatial Information and Data Distribution for Classification of PolSAR Image

, 2019
The distribution of data plays a key role in the designing of a machine learning model. Therefore, this paper proposes a novel auto encoder network based on the distribution of polarimetric synthetic aperture radar (PolSAR) data matrix.
Shuang Wang, Licheng Jiao, Jianlong Wang, Biao Hou   +3 more
core   +1 more source

Multi-Domain Fusion Graph Network for Semi-Supervised PolSAR Image Classification

, 2022
The expensive acquisition of labeled data limits the practical use of supervised learning on polarimetric synthetic aperture radar (PolSAR) image analysis.
Rui Tang, Fangling Pu, Xin Xu, Rui Yang, Zhaozhuo Xu   +4 more
core   +1 more source

Polarimetric Contextual Classification of PolSAR Images Using Sparse Representation and Superpixels

Remote Sensing, 2014
In recent years, sparse representation-based techniques have shown great potential for pattern recognition problems. In this paper, the problem of polarimetric synthetic aperture radar (PolSAR) image classification is investigated using sparse ...
Jilan Feng, Zongjie Cao, Yiming Pi
doaj   +1 more source

PolSAR Image Classification with Active Complex-Valued Convolutional-Wavelet Neural Network and Markov Random Fields

PolSAR image classification has attracted extensive significant research in recent decades. Aiming at improving PolSAR classification performance with speckle noise, this paper proposes an active complex-valued convolutional-wavelet neural network by ...
Lu Liu, Yongxiang Li
core   +1 more source

Lightweight Complex-Valued Siamese Network for Few-Shot PolSAR Image Classification

Complex-valued convolutional neural networks (CVCNNs) have demonstrated strong capabilities for polarimetric synthetic aperture radar (PolSAR) image classification by effectively integrating both amplitude and phase information inherent in polarimetric ...
Lei Liu, Yinyin Jiang, Rongzhen Du, Wanying Song, Peng Zhang, Zhenxi Zhang   +5 more
core   +1 more source

Adaptive scale segmentation algorithm for polarimetric SAR image

The Journal of Engineering, 2019
Polarimetric SAR (PolSAR) data can be characterised by scattering matrix, which contains four elements. It is difficult to merge all the elements of the scattering matrix for segmentation.
Yifan Xu, Aifang Liu, Long Huang
doaj   +1 more source

A novel semicoupled projective dictionary pair learning method for PolSAR image classification

, 2019
Polarimetric synthetic aperture radar (PolSAR) image classification plays an important role in remote sensing image processing. In recent years, stacked auto-encoder (SAE) has obtained a series of excellent results in PolSAR image classification.
Chen, Yanqiao, Jiao, Licheng, Li, Yangyang, Ren, Bo, Marturi, Naresh, Zhang, Dan, Li, Lingling   +6 more
core   +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

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

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