SBCS-Net: Sparse Bayesian and Deep Learning Framework for Compressed Sensing in Sensor Networks by Xianwei Gao, Xiang Yao, Bi Chen, Honghao Zhang

“…This framework innovatively expands the iterative process of sparse Bayesian compressed sensing using convolutional neural networks and Transformer. …”
Get full text

Phaseless Diagnosis and Pattern Correction of Faulty Antenna Arrays via Advanced Bayesian Compressive Sensing Approaches by Zi An Wang, Ping Li

“…This paper presents an integrated approach for diagnosing and correcting faults in antenna arrays using a Bayesian compressive sensing (BCS) method. The proposed diagnostic technique effectively identifies both ON-OFF and partial faults with limited phaseless measurement data. …”
Get full text

Time-varying channel estimation in reconfigurable intelligent surface assisted communication system by Kai SHAO, Ben LU, Guangyu WANG

“…Aiming at the key problems need to be solved, such as cascade channel sparse representation, time-varying channel parameter tracking and signal reconstruction, for time-varying cascade channels estimation of reconfigurable intelligent surface (RIS) assisted communication system, a Khatri-Rao and hierarchical Bayesian Kalman filter (KR-HBKF) algorithm was proposed.Firstly, the Khatri-Rao product and Kronecker product transformations were used to obtain the sparse representation of RIS cascaded channels based on the sparse characteristics of channels, thus the RIS cascaded channel estimation problem was transformed into a low-dimensional sparse signal recovery problem.Then, according to the state evolution model of RIS cascaded channel, the time correlation parameter was introduced into the prediction model of HBKF algorithm, and the improved HBKF was applied to solve the problem of time-varying channel parameter tracking and signal reconstruction for completing the time-varying cascaded channels estimation.The sparsity and time correlation of the channel were comprehensively considered in the KR-HBKF algorithm, thus better estimation accuracy could be obtained with small pilot overhead.Compared with the traditional compressed sensing algorithm, the simulation results show that the proposed algorithm has about 5 dB estimated performance improvement, and better robustness performance under different time-varying channel conditions.…”
Get full text

FY-4A/AGRI Cloud Detection Method Based on Naive Bayesian Algorithm by Guo Xuexing, Qu Jianhua, Ye Lingmeng, Han Min, Shi Mojie

“…Optical remote sensing cloud detection is the foundation for subsequent quantitative remote sensing and applications. …”
Get full text

Different lockdowns and theft: a Bayesian analysis of COVID-19's impact on urban crime in ZG City, China by Xinhua Huang, Dongping Long, Heng Liu

Get full text

Refined Urban Functional Zones Identification via Empirical Bayesian Kriging: A POI-Weighted Scoring Innovation by Xuan Du, Yisha Pan, Xiaoyan Yang, Longgao Chen, Liangchen Liu, Ying Lin

“…However, achieving high precision and comprehensive identification of UFZs has been challenging. …”
Get full text

Probabilistic machine learning-based phytoplankton abundance using hyperspectral remote sensing by Do Hyuck Kwon, Jung Min Ahn, Jong Cheol Pyo, Jiye Lee, Ather Abbas, Sanghyun Park, Kyunghyun Kim, Hyuk Lee, Kyung Hwa Cho

“…Utilizing a Bayesian neural network and natural gradient-boosting algorithm, we simulated phytoplankton abundance using airborne remote sensing data. …”
Get full text

Satellite Image Price Prediction Based on Machine Learning by Linhan Yang, Zugang Chen, Guoqing Li

Get full text

On the Use of Azimuth Cutoff for Sea Surface Wind Speed Retrieval From SAR by Yuting Zhu, Giuseppe Grieco, Jiarong Lin, Marcos Portabella, Xiaoqing Wang

“…This study introduces a Bayesian inversion algorithm that incorporates azimuth cutoff wavelength information—a parameter previously underutilized and highly sensitive to varying wind conditions. …”
Get full text

A Robust Tracking Method for Aerial Extended Targets with Space-Based Wideband Radar by Linlin Fang, Yuxin Hu, Lihua Zhong, Lijia Huang

Get full text

Collaborative altitude-adaptive reinforcement learning for active search with unmanned aerial vehicle swarms by XIAO Zijian, Chen-Chun Hsia, XU Yanggang, REN Jiyuan, CHEN Xinlei

Get full text

Estimating comprehensive growth index for drip-irrigated spring maize in junggar basin via satellite imagery and machine learning by Mingjie Ma, Jinghua Zhao, Tingrui Yang, Feng Liu, Yingying Yuan, Shijiao Ma, Zikang Chang

“…The development of remote sensing technology provides a new perspective for modern agricultural crop growth monitoring. …”
Get full text

Integrated Correction of Nonlinear Dynamic Drift in Terrestrial Mobile Gravity Surveys: A Comparative Study Based on the Northeastern China Gravity Monitoring Network by Zhaohui Chen, Jinzhao Liu

Get full text

Performance of the Earth Explorer 11 SeaSTAR Mission Candidate for Simultaneous Retrieval of Total Surface Current and Wind Vectors by Adrien C. H. Martin, Christine P. Gommenginger, Daria Andrievskaia, Petronilo Martin-Iglesias, Alejandro Egido

Get full text

Deep learning-driven 3D marine nitrate estimation: uncertainty mitigation through underwater signal exploitation and label augmentation by Xiang Yu, Guodong Fan, Jinjiang Li

Get full text

PolSAR Forest Height Estimation Enhancement With Polarimetric Rotation Domain Features and Multivariate Sensitivity Analysis by Fu-Gen Jiang, Ming-Dian Li, Si-Wei Chen

Get full text

Comparative assessment of machine learning algorithms for retrieving colored dissolved organic matter (CDOM) from Sentinel-2/MSI images in the coastal waters of the Persian Gulf by Bonyad Ahmadi, Mehdi Gholamalifard, Seyed Mahmoud Ghasempouri, Tiit Kutser

“…The MDN achieved an RMSLE of 0.47 (17.5 % improvement over MLP, 14.5 % over SVM) and reduced systematic bias (SSPB) by 26.12 units compared to Bayesian Ridge Regression (BRR), outperforming conventional models like SVM (MAE = 0.61, RMSLE = 0.55). …”
Get full text

The Study on Landslide Hazards Based on Multi-Source Data and GMLCM Approach by Zhifang Zhao, Zhengyu Li, Penghui Lv, Fei Zhao, Lei Niu

Get full text

Spatiotemporal Characteristics and Influencing Factors of PM_2.5 Levels in Lianyungang: Insights from a Multidimensional Analysis by Xue Li, Haihong He, Dewei Wang, Wenli Qiao, Chunli Liu, Yiming Sun, Lulu Li, Shuting Han, Guozhen Zha

Get full text

Uncertainty Quantification of Geophysical and Hydrologic Parameters Estimated From Borehole Nuclear Magnetic Resonance Data by Burke J. Minsley, Stephanie N. Phillips, Stephanie R. James

Get full text